Search results for: bullying recognition

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

Abstract:

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 150

Authors: Kamyar Fakhr, Roozbeh Salmani

Abstract:

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 218

Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira

Abstract:

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 156

Authors: Kiyoko Yoshimura, Yasunobu Kino

Abstract:

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 112

Authors: Ilia Zharikov, Philipp Nikitin, Ilia Vasiliev, Vladimir Dokholyan

Abstract:

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 172

Authors: Poonamdeep kaur

Abstract:

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 191

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

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 365

Authors: Mohammed Arif, Abdessalam Kifouche

Abstract:

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 71

Authors: Shiyin He, Zheng Huang

Abstract:

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 188

Authors: C. V. Aravinda, H. N. Prakash

Abstract:

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 494

Authors: Prakash Singh

Abstract:

In this exploratory qualitative case study, the voices of female teachers are captured that describe their fear of failure in coping with their daily anxieties, stresses, and tensions in their classrooms. When teachers are usually appointed, the curriculum forms the heart of all their professional obligations. The policy of quality and equality of education for all learners is a must as part of these deliberations, otherwise it would spell the inevitable failure for teachers. Yet, how often have teachers been asked whether they are happy during their professional tenure. Research affirms that this question is not a priority, seeing that the happiness of learners and the educational administrators enjoy precedence. Teachers are often subject to undue pressures and tensions because of environmental factors that extends beyond the curriculum. School violence, bullying, drug abuse, and gangsters are not uncommon to the school milieu, no matter where such schools can be located. In this case study, the voices of female teachers find space concerning their experiences of tobephobia (TBP). The questions that inevitably arise are: Are the educational authorities aware of the effects of TBP in education? What can be done to arrest and eliminate the debilitating effects of TBP? This exploratory study contributes to the growing concerns of TBP in education. It is therefore imperative that the effects of TBP on human resources in education must be accentuated so that meaningful solutions can be found to address challenging educational issues such as school violence, bullying, and drug abuse amongst learners.

Keywords: curriculum, female teachers, school violence, tobephobia

Procedia PDF Downloads 404

Authors: John Lorenzo Bautista, Yoon-Joong Kim

Abstract:

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 480

Authors: Svitov David, Alyamkin Sergey

Abstract:

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 146

Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

Abstract:

Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

Procedia PDF Downloads 405

Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

Abstract:

In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

Procedia PDF Downloads 372

Authors: Bin Liu

Abstract:

Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

Procedia PDF Downloads 161

Authors: Kahandawala Arachchige Thani Chathurika Kahandawala

Abstract:

This research is attempted to analyse, Sri Lanka’s current situation regarding the recognition and enforcement of international commercial arbitration awards. Sri Lanka has been involved with commercial arbitration for a long time period. But there are good and bad legal practices in place in proceedings in Sri Lanka legal system. The common perception and reality of Sri Lanka’s arbitration law and practices regarding recognition and enforcement of international arbitral awards is far behind the international standards. Therefore arbitration as a dispute resolution method has become a time-consuming and costly method in Sri Lanka. This research is employed with the qualitative method based on both primary and secondary resources. This carried out the comparative analysis of recognition and enforcement in international arbitration laws established jurisdiction in Singapore and the United Kingdom, which are known as best counties as a seat of arbitration in Asia and Europe. International conventions, act and all the legal proceedings regarding recognition and enforcement of an international arbitral award in Sri Lanka are going to be discussed in the research. In the Jurisdiction of Sri Lanka, critically need to value an international arbitral award in the domestic legal system. Therefore an award has to be recognised in Sri Lanka. Otherwise, it doesn’t have any value. After recognizing it, court can enforce it. This research intends to provide a comparative analysis to overcome the drawbacks.

Keywords: arbitration, alternative dispute method, recognition and enforcement, foreign arbitral awards, Sri Lankan legal system, arbitral award in Singapore

Procedia PDF Downloads 171

Authors: M. Dabirinezhad, M. Bayat Pour, A. Dabirinejad

Abstract:

Recognition of the color spectrum of the teeth plays a significant role in the dental laboratories to produce dentures. Since there are various types and colours of teeth for each patient, there is a need to specify the exact and the most suitable colour to produce a denture. Usually, dentists utilize pallets to identify the color that suits a patient based on the color of the adjacent teeth. Consistent with this, there can be human errors by dentists to recognize the optimum colour for the patient, and it can be annoying for the patient. According to the statistics, there are some claims from the patients that they are not satisfied by the colour of their dentures after the installation of the denture in their mouths. This problem emanates from the lack of sufficient accuracy during the colour recognition process of denture production. The colour recognition pen (CRP) is a technology to distinguish the colour spectrum of the intended teeth with the highest accuracy. CRP is equipped with a sensor that is capable to read and analyse a wide range of spectrums. It is also connected to a database that contains all the spectrum ranges, which exist in the market. The database is editable and updatable based on market requirements. Another advantage of this invention can be mentioned as saving time for the patients since there is no need to redo the denture production in case of failure on the first try.

Keywords: colour recognition pen, colour spectrum, dental laboratory, denture

Procedia PDF Downloads 198

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

Procedia PDF Downloads 155

Authors: Jadisha Cornejo, Helio Pedrini

Abstract:

Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

Procedia PDF Downloads 182

Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

Abstract:

A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

Procedia PDF Downloads 368

Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

Abstract:

This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

Procedia PDF Downloads 667

Authors: Ahmad Alwosheel, Ahmed Alqaraawi

Abstract:

This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

Procedia PDF Downloads 380

Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

Procedia PDF Downloads 259

Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

Abstract:

Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

Procedia PDF Downloads 331

Authors: Vishwa Joshi

Abstract:

The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

Procedia PDF Downloads 495

Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

Abstract:

Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

Procedia PDF Downloads 65

Authors: Maria Pavlova

Abstract:

In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

Procedia PDF Downloads 218

Authors: Shih-Yu Lo

Abstract:

Stereotypes exist in almost every society, affecting how people interact with each other. However, to our knowledge, the influence of stereotypes was rarely explored in the context of basic perceptual processes. This study aims to explore how the gender stereotype affects object recognition. Participants were presented with a series of scene pictures, followed by a target display with a man or a woman, holding a weapon or a non-weapon object. The task was to identify whether the object in the target display was a weapon or not. Although the gender of the object holder could not predict whether he or she held a weapon, and was irrelevant to the task goal, the participant nevertheless tended to identify the object as a weapon when the object holder was a man than a woman. The analysis based on the signal detection theory showed that the stereotype effect on object recognition mainly resulted from the participant’s bias to make a 'weapon' response when a man was in the scene instead of a woman in the scene. In addition, there was a trend that the participant’s sensitivity to differentiate a weapon from a non-threating object was higher when a woman was in the scene than a man was in the scene. The results of this study suggest that the irrelevant social cues implied in the visual scene can be very powerful that they can modulate the basic object recognition process.

Keywords: gender stereotype, object recognition, signal detection theory, weapon

Procedia PDF Downloads 209

Authors: Mina Youssef Makram Ibrahim

Abstract:

Engineering identity contributes to the professional and academic sustainability of female engineers. Recognizability is an important factor that shapes an engineer's identity. People who are deprived of real recognition often fail to create a positive identity. This study draws on Hornet’s recognition theory to identify factors that influence female civil engineers' sense of recognition. Over the past decade, a survey was created and distributed to 330 graduate students in the Department of Civil, Civil and Environmental Engineering at Iowa State University. Survey items include demographics, perceptions of a civil engineer's identity, and factors that influence recognition of a civil engineer's identity, such as B. Opinions about society and family. Descriptive analysis of survey responses revealed that perceptions of civil engineering varied significantly. The definitions of civil engineering provided by participants included the terms structure, design and infrastructure. Almost half of the participants said the main reason for studying Civil Engineering was their interest in the subject, and the majority said they were proud to be a civil engineer. Many study participants reported that their parents viewed them as civil engineers. Institutional and operational treatment was also found to have a significant impact on the recognition of women civil engineers. Almost half of the participants reported feeling isolated or ignored at work because of their gender. This research highlights the importance of recognition in developing the identity of women engineers.

Keywords: civil service, hiring, merit, policing civil engineering, construction, surveying, mapping, pile civil service, Kazakhstan, modernization, a national model of civil service, civil service reforms, bureaucracy civil engineering, gender, identity, recognition

Procedia PDF Downloads 62