Search results for: distant named entity recognition
2612 Bird-Adapted Filter for Avian Species and Individual Identification Systems Improvement
Authors: Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Pruchova, Pavel Linhart, Ludek Muller, Dana Jirotkova
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One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.Keywords: avian audiogram, bird individual identification, bird song processing, bird species recognition, filter bank
Procedia PDF Downloads 3822611 Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features
Authors: Kyi Pyar Zaw, Zin Mar Kyu
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Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.Keywords: chain code frequency, character recognition, feature extraction, features matching, segmentation
Procedia PDF Downloads 3112610 Intelligent Human Pose Recognition Based on EMG Signal Analysis and Machine 3D Model
Authors: Si Chen, Quanhong Jiang
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In the increasingly mature posture recognition technology, human movement information is widely used in sports rehabilitation, human-computer interaction, medical health, human posture assessment, and other fields today; this project uses the most original ideas; it is proposed to use the collection equipment for the collection of myoelectric data, reflect the muscle posture change on a degree of freedom through data processing, carry out data-muscle three-dimensional model joint adjustment, and realize basic pose recognition. Based on this, bionic aids or medical rehabilitation equipment can be further developed with the help of robotic arms and cutting-edge technology, which has a bright future and unlimited development space.Keywords: pose recognition, 3D animation, electromyography, machine learning, bionics
Procedia PDF Downloads 682609 Smartphone-Based Human Activity Recognition by Machine Learning Methods
Authors: Yanting Cao, Kazumitsu Nawata
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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.Keywords: smart sensors, human activity recognition, artificial intelligence, SVM
Procedia PDF Downloads 1392608 Multimodal Employee Attendance Management System
Authors: Khaled Mohammed
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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio
Procedia PDF Downloads 1502607 Human Gait Recognition Using Moment with Fuzzy
Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain
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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments
Procedia PDF Downloads 7522606 A Conglomerate of Multiple Optical Character Recognition Table Detection and Extraction
Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar
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Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation
Procedia PDF Downloads 1382605 Recognition of Cursive Arabic Handwritten Text Using Embedded Training Based on Hidden Markov Models (HMMs)
Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss
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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.Keywords: recognition, handwriting, Arabic text, HMMs, embedded training
Procedia PDF Downloads 3462604 The Integration of Digital Humanities into the Sociology of Knowledge Approach to Discourse Analysis
Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García
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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis
Procedia PDF Downloads 2182603 The Role of Virtual Reality in Mediating the Vulnerability of Distant Suffering: Distance, Agency, and the Hierarchies of Human Life
Authors: Z. Xu
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Immersive virtual reality (VR) has gained momentum in humanitarian communication due to its utopian promises of co-presence, immediacy, and transcendence. These potential benefits have led the United Nations (UN) to tirelessly produce and distribute VR series to evoke global empathy and encourage policymakers, philanthropic business tycoons and citizens around the world to actually do something (i.e. give a donation). However, it is unclear whether or not VR can cultivate cosmopolitans with a sense of social responsibility towards the geographically, socially/culturally and morally mediated misfortune of faraway others. Drawing upon existing works on the mediation of distant suffering, this article constructs an analytical framework to articulate the issue. Applying this framework on a case study of five of the UN’s VR pieces, the article identifies three paradoxes that exist between cyber-utopian and cyber-dystopian narratives. In the “paradox of distance”, VR relies on the notions of “presence” and “storyliving” to implicitly link audiences spatially and temporally to distant suffering, creating global connectivity and reducing perceived distances between audiences and others; yet it also enables audiences to fully occupy the point of view of distant sufferers (creating too close/absolute proximity), which may cause them to feel naive self-righteousness or narcissism with their pleasures and desire, thereby destroying the “proper distance”. In the “paradox of agency”, VR simulates a superficially “real” encounter for visual intimacy, thereby establishing an “audiences–beneficiary” relationship in humanitarian communication; yet in this case the mediated hyperreality is not an authentic reality, and its simulation does not fill the gap between reality and the virtual world. In the “paradox of the hierarchies of human life”, VR enables an audience to experience virtually fundamental “freedom”, epitomizing an attitude of cultural relativism that informs a great deal of contemporary multiculturalism, providing vast possibilities for a more egalitarian representation of distant sufferers; yet it also takes the spectator’s personally empathic feelings as the focus of intervention, rather than structural inequality and political exclusion (an economic and political power relations of viewing). Thus, the audience can potentially remain trapped within the minefield of hegemonic humanitarianism. This study is significant in two respects. First, it advances the turn of digitalization in studies of media and morality in the polymedia milieu; it is motivated by the necessary call for a move beyond traditional technological environments to arrive at a more novel understanding of the asymmetry of power between the safety of spectators and the vulnerability of mediated sufferers. Second, it not only reminds humanitarian journalists and NGOs that they should not rely entirely on the richer news experience or powerful response-ability enabled by VR to gain a “moral bond” with distant sufferers, but also argues that when fully-fledged VR technology is developed, it can serve as a kind of alchemy and should not be underestimated merely as a “bugaboo” of an alarmist philosophical and fictional dystopia.Keywords: audience, cosmopolitan, distant suffering, virtual reality, humanitarian communication
Procedia PDF Downloads 1352602 Community Opinions on Cable Car System Construction at Upper Esaan Wild Animal Adventure Park (Khon Kaen – Udon Thani) in Khao Suan Kwang District, Khon Kaen Province (Khon Kaen Zoo), Thailand
Authors: Ruchirat Patanathabutr
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This applied research has adopted descriptive social science research methodology to interpret, analyze and assess the data and used descriptive analysis to present the research results. The objective of this research is to investigate the behaviors and opinions on the service and construction of cable car system at the Upper Esaan Wild Animal Adventure Park (Khon Kaen – Udon Thani) in Khao Suan Kwang District, Khon Kaen Province (Khon Kaen Zoo) of people in the local and distant communities as well as the service users. The research results have revealed that the main target group is the residents in the upper northeastern region of Thailand, especially those who have resided in the immediate vicinity of the cable car project and in nearby districts for more than 10 years. They are men and women at the age of 20-60 with high school diploma and higher levels of education, working as traders/entrepreneurs, government officers/state enterprise employees, and freelancers/self-employed, with the average monthly income of no more than 30,000 baht. Khon Kaen Zoo should improve its 4 organizational images as a tourist attraction, an animal display enclosure, an educational institution and as a provincial symbol; however, the zoo should mainly be presented as an important tourist attraction. The service should focus on maintaining the service standards in both the animal display area and the ocean park. The attention should also be directed at the types and numbers of animals, service quality, service fee, convenient access and transportation, promotions and the standards of other services. Regarding the community involvement in the cable car system construction project, it is strongly agreed that there should be a cable car service between the animal display area and the ocean park and a round-trip ticket should cost 20 baht, 50 baht or 100 baht, respectively. Khon Kaen Zoo or responsible entity must provide related groups of people, such as people in the local and distant communities as well as the service users, with accurate information about the community management guidelines. This is because the community opinions have showed the uncertainty about the cable car system construction at Khon Kaen Zoo and the 4 principles of management, including planning, organizing, leading and controlling, are indicated as uncertain as there is no statistically significant difference at 0.05. In addition, the social, economic, and environmental impacts of the cable car system construction at Khon Kaen Zoo on the communities must be considered carefully.Keywords: community opinion, cable car system, Khon Kaen Zoo, Thailand
Procedia PDF Downloads 3532601 A Study on Local Wisdom towards Career Building of People in Kamchanoad Community
Authors: Phusit Phukamchanoad, Thananya Santithammakul, Suwaree Yordchim, Pennapa Palapin
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This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.Keywords: local wisdoms, careers, Kamchanoad Community, career building
Procedia PDF Downloads 3082600 Fitness Action Recognition Based on MediaPipe
Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin
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MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize the human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.Keywords: computer vision, MediaPipe, adaptive boosting, fast dynamic time warping
Procedia PDF Downloads 1062599 Words Spotting in the Images Handwritten Historical Documents
Authors: Issam Ben Jami
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Information retrieval in digital libraries is very important because most famous historical documents occupy a significant value. The word spotting in historical documents is a very difficult notion, because automatic recognition of such documents is naturally cursive, it represents a wide variability in the level scale and translation words in the same documents. We first present a system for the automatic recognition, based on the extraction of interest points words from the image model. The extraction phase of the key points is chosen from the representation of the image as a synthetic description of the shape recognition in a multidimensional space. As a result, we use advanced methods that can find and describe interesting points invariant to scale, rotation and lighting which are linked to local configurations of pixels. We test this approach on documents of the 15th century. Our experiments give important results.Keywords: feature matching, historical documents, pattern recognition, word spotting
Procedia PDF Downloads 2692598 Recognition of Tifinagh Characters with Missing Parts Using Neural Network
Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui
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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN
Procedia PDF Downloads 3252597 Exploratory Analysis of A Review of Nonexistence Polarity in Native Speech
Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori
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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing
Procedia PDF Downloads 1212596 Lightweight Hybrid Convolutional and Recurrent Neural Networks for Wearable Sensor Based Human Activity Recognition
Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang
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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor
Procedia PDF Downloads 1422595 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network
Authors: Kamyar Fakhr, Roozbeh Salmani
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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.Keywords: biometric system, convolutional neural network, cyber-attack, secure
Procedia PDF Downloads 2112594 ANAC-id - Facial Recognition to Detect Fraud
Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira
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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision
Procedia PDF Downloads 1482593 Effects of Recognition of Customer Feedback on Relationships between Emotional Labor and Job Satisfaction: Focusing On Call Centers That Offer Professional Services
Authors: Kiyoko Yoshimura, Yasunobu Kino
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Focusing on professional call centers where workers with expertise perform services, this study aims to clarify the relationships between emotional labor and job satisfaction and the effects of recognition of customer feedback. Since the professional call center operators consist of professional license holders (qualification holders) and those who do not (non-holders), the following three points are analyzed in the two groups by using covariance structure analysis and simultaneous multi-population analysis: 1) The relationship between emotional labor and job satisfaction, 2) customer feedback and job satisfaction, and 3) The intermediation effect between the emotional labor of customer feedback and job satisfaction. The following results are obtained: i) no direct effect is found between job satisfaction and emotional labor for qualification holders and non-holders, ii) for qualification holders and non-holders, recognition of positive feedback and recognition of negative feedback had positive and negative effects on job satisfaction, respectively, iii) for qualification and non-holders, "consideration for colleagues" influences job satisfaction by recognizing positive feedback, and iv) only for qualification holders, the factors "customer-oriented emotional expression" and "emotional disharmony" have a positive and negative effect on job satisfaction, respectively, through recognition of positive feedback and recognition of negative feedback.Keywords: call center, emotional labor, professional service, job satisfaction, customer feedback
Procedia PDF Downloads 932592 Distorted Document Images Dataset for Text Detection and Recognition
Authors: Ilia Zharikov, Philipp Nikitin, Ilia Vasiliev, Vladimir Dokholyan
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With the increasing popularity of document analysis and recognition systems, text detection (TD) and optical character recognition (OCR) in document images become challenging tasks. However, according to our best knowledge, no publicly available datasets for these particular problems exist. In this paper, we introduce a Distorted Document Images dataset (DDI-100) and provide a detailed analysis of the DDI-100 in its current state. To create the dataset we collected 7000 unique document pages, and extend it by applying different types of distortions and geometric transformations. In total, DDI-100 contains more than 100,000 document images together with binary text masks, text and character locations in terms of bounding boxes. We also present an analysis of several state-of-the-art TD and OCR approaches on the presented dataset. Lastly, we demonstrate the usefulness of DDI-100 to improve accuracy and stability of the considered TD and OCR models.Keywords: document analysis, open dataset, optical character recognition, text detection
Procedia PDF Downloads 1642591 A Critical Analysis of the Concept of Unconscionable Abuse under the South African Company Law
Authors: Siphethile Phiri
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Although a company is a legal entity with separate legal personality, the courts are empowered to review and set aside the personality of a company on the ground of ‘an unconscionable abuse’. The process is called piercing of the corporate veil. Of interesting note however, it is controversial as to what the concept of ‘unconscionable abuse’ entails. The purpose of this study is to explore this concept in an attempt to understand its proper meaning and how it bears on the powers of the company director to take decision on behalf of the company as a juristic entity. Given the confounding provision, an attempt is made to identify the circumstances in which the courts may pierce the corporate veil and also to investigate the extent to which the courts can do so. The results of this study show that the term unconscionable abuse is a legislative innovation to justify the court’s interference with the separate legal personality functions of a company.Keywords: company law, unconscionable abuse, director, companies act
Procedia PDF Downloads 2862590 Recognition and Enforcement of Foreign Decree Divorces in India with Special Reference to the Hindu Marriage Act, 1955
Authors: Poonamdeep kaur
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With the increase in number of Non-Resident Indian marriages there is also increase in foreign decree divorces which inevitably causes the problem of recognition and enforcement of foreign judgments in India. The Hindus in India are governed by the Hindu Marriage Act, 1956. According to the said Act the courts in India have jurisdiction to try the matrimonial dispute if the marriage is performed in India or the parties to the marriage have domicile in India irrespective of their nationality status. But, sometimes one of the parties to the marriage whose marriage is solemnized in India obtains divorce in foreign courts and prays for the recognition and enforcement of such divorce in India. In such case section 13 of the Indian Civil Procedure Code, 1908, comes into play for the recognition and enforcement of foreign divorces in India. The section makes a foreign judgment conclusive in India subject to the fulfilment of certain conditions. Even if a foreign decree divorce is given on personal connecting factors of the parties to the matrimonial dispute like domicile, such divorce may still be refused recognition in India by virtue of section 13 of the Indian Civil Procedure Code, 1908. It is a universal truth that municipal law of countries is not the same throughout the world. Comity plays an important role in recognition and enforcing a foreign judgment, but, now in India the principle is not applied mechanically as the divorce matter is dealt strictly with regard to Indian Law. So in this paper there will be deep analysis of Indian case laws relating to recognition and enforcement of foreign divorces and based on this a comparative study will be made with the laws of Canada and England on the same subject to find out whether the Indian law on recognition and Enforcement of foreign judgment are in line with the laws of Canada and England and whether in recent years the Indian courts have evolved some new principles of private international law to deal with limping marriages. At last conclusions will be drawn out from the comparative study and suggestions would be given to make the rules of recognition and enforcement of foreign judgments on divorce more certain.Keywords: divorce, foreign decree, private international law, recognition and enforcement of foreign judgment
Procedia PDF Downloads 1872589 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis
Authors: Amir Hajian, Sepehr Damavandinejadmonfared
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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)
Procedia PDF Downloads 3592588 Arabic Handwriting Recognition Using Local Approach
Authors: Mohammed Arif, Abdessalam Kifouche
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Optical character recognition (OCR) has a main role in the present time. It's capable to solve many serious problems and simplify human activities. The OCR yields to 70's, since many solutions has been proposed, but unfortunately, it was supportive to nothing but Latin languages. This work proposes a system of recognition of an off-line Arabic handwriting. This system is based on a structural segmentation method and uses support vector machines (SVM) in the classification phase. We have presented a state of art of the characters segmentation methods, after that a view of the OCR area, also we will address the normalization problems we went through. After a comparison between the Arabic handwritten characters & the segmentation methods, we had introduced a contribution through a segmentation algorithm.Keywords: OCR, segmentation, Arabic characters, PAW, post-processing, SVM
Procedia PDF Downloads 512587 Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method
Authors: Shiyin He, Zheng Huang
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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet
Procedia PDF Downloads 1782586 Kannada HandWritten Character Recognition by Edge Hinge and Edge Distribution Techniques Using Manhatan and Minimum Distance Classifiers
Authors: C. V. Aravinda, H. N. Prakash
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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages
Procedia PDF Downloads 4882585 An Automatic Speech Recognition Tool for the Filipino Language Using the HTK System
Authors: John Lorenzo Bautista, Yoon-Joong Kim
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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition
Procedia PDF Downloads 4732584 Plasmablastic Lymphoma a New Entity in Patients with HIV Infections
Authors: Rojith K. Balakrishnan
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Plasmablastic lymphoma (PBL) is an uncommon, recently described B-cell derived lymphoma that is most commonly seen in patients with Human Immunodeficiency Virus (HIV) infection. Here we report a case of PBL in a 35 year old man with HIV who presented with multiple subcutaneous swellings all over the body and oral mucosal lesions.The biopsy report was suggestive of Diffuse Large B Cell Lymphoma. Immunohistochemistry was done which showed, lymphoma cells, positive for MUM1, CD 138, and VS 38. The proliferation index (MIB) was 95%. Final report was consistent with the diagnosis of Plasmablastic Lymphoma. The lesion completely regressed after treatment with systemic chemotherapy. Up to date, only a few cases of plasmablastic lymphoma have been reported from India. Increased frequency of this lymphoma in HIV patients and rarity of the tumour, along with rapid response of the same to chemotherapy, make this case a unique one. Hence the knowledge about this new entity is important for clinicians who deal with HIV patients.Keywords: human immunodeficiency virus (HIV), oral cavity lesion, plasmablastic lymphoma, subcutaneous swelling
Procedia PDF Downloads 2642583 MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax
Authors: Svitov David, Alyamkin Sergey
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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.Keywords: ArcFace, distillation, face recognition, margin-based softmax
Procedia PDF Downloads 141