Search results for: visual image

Authors: Ya-Chuan Tseng, Hsin-Yi Liu, Meei-Fang Lou, Guey-Shiun Huang

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Purpose: Sensory impairments are common in older adults. Hearing and visual impairments affect their physical and mental health and quality of life (QOL) adversely. However, systematic reviews of the relationship between hearing impairment, visual impairment, dual sensory impairment and quality of life are scarce. The purpose of this systematic review was to determine the relationship between hearing impairment, visual impairment, dual sensory impairment and quality of life. Methods: Searches of EMBASE, PubMed, CINAHL, MEDLINE, Cochrane Library and Airiti Library were conducted between January 2006 and December 2017 using the keywords ‘quality of life,’ ‘life satisfaction,’ ‘well-being,’ ‘hearing impairment’ and ‘visual impairment’ Two authors independently assessed methodologic quality using a modified Downs and Black tool. Data were extracted by the first author and then cross-checked by the second author. Results: Twenty-three studies consisting mostly of community-dwelling older adults were included in our review. Sensory impairment was found to be in significant association with quality of life, with an increase in hearing impairment or visual impairment severity resulting in a lower quality of life. Quality of life for dual sensory impairment was worse than for hearing impairment or visual impairment individually. Conclusions: A significant association was confirmed between hearing impairment, visual impairment, dual sensory impairment and quality of life. Our review can be used to enhance health care personnel’s understanding of sensory impairment in older adults and enable healthcare personnel to actively assess older adults’ sensory functions so that they can help alleviate the negative impact of sensory impairments on QOL in older adults.

Keywords: nursing, older adults, quality of life, systematic review, hearing impairment, visual impairment

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Authors: Francia Martinez

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This study documents and demonstrates the profound impact of the high status of American English and culture in Colombian commercial landscape due to the globalization and commodification of English. It also documents and describes how Colombian advertisers make use of various language and visual mechanisms in the commercial linguistic landscape to convey messages, create an image with which the target audience can identify, and build a relationship with that target audience. The data (in the form of pictures) were collected in different cities in Colombia and were classified and organized into different categories for the reliability and validity of the analysis. The research questions were: do the ubiquity and high status of American English and culture play a major role in the Colombian commercial linguistic landscape? If so, how?, what roles do national and local culture and language (Spanish) play in the commercial linguistic landscape?, and what different linguistic and visual strategies do Colombian advertisers employ to reach their target audience? Based on data analysis and results, American and local culture and icons play a major role when Colombian advertisers create and design their commercial logos and ads to get consumers’ attention and establish a rapport with them in a successful way. In order to achieve their objectives, Colombian advertisers rely on creative linguistic and visual techniques in their ads, such as puns, humor, irony, comparisons, metaphors, mocking, exaggeration, parody, personification, sarcasm, satire, allusion, onomatopoeias, and imitation (copycat or cloning).

Keywords: Colombian ads, linguistic landscape, rhetorical devices, sociolinguistics

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Mikyung Bak

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The dokkaebi, a beloved icon of Korean culture, is represented as an elf, goblin, monster, dwarf, or any similar creature in different media, such as animated shows, comics, soap operas, and movies. It is often described as a mythical creature with a horn or horns and long teeth, wearing tiger-skin pants or a grass skirt, and carrying a magic stick. Many Korean researchers agree on the similarity of the image of the Korean dokkaebi with that of the Japanese oni, a view that is regard as negative from an anti-colonial or nationalistic standpoint. They cite such similarity between the two mythical creatures as evidence that Japanese colonialism persists in Korea. The debate on the originality of dokkaebi’s visual representation is an issue that must be addressed urgently. This research demonstrates through a diagram the plurality of interpretations of dokkaebi’s visual representations in what are considered ‘authentic’ images of dokkaebi in Korean art and culture. This diagram presents the opinions of four major groups in the debate, namely, the scholars of Korean literature and folklore, art historians, authors, and artists. It also shows the creation of new dokkaebi visual representations in popular media, including those influenced by the debate. The diagram further proves that dokkaebi’s representations varied, which include the typical persons or invisible characters found in Korean literature, original Korean folk characters in traditional art, and even universal spirit characters. They are also visually represented by completely new creatures as well as oni-based mythical beings and the actual oni itself. The earlier dokkaebi representations were driven by the creation of a national ideology or national cultural paradigm and, thus, were more uniform and protected. In contrast, the more recent representations are influenced by the Korean industrial strategy of ‘cultural economics,’ which is concerned with the international rather than the domestic market. This recent Korean cultural strategy emphasizes diversity and commonality with the global culture rather than originality and locality. It employs traditional cultural resources to construct a global image. Consequently, dokkaebi’s recent representations have become more common and diverse, thereby incorporating even oni’s characteristics. This argument has rendered the grounds of the debate irrelevant. The dokkaebi has been used recently for tourist marketing purposes, particularly in revitalizing interest in regions considered the cradle of various traditional dokkaebi tales. These campaign strategies include the Jeju-do Dokkaebi Park, Koksung Dokkaebi Land, as well as the Taebaek and Sokri-san Dokkaebi Festivals. Almost dokkaebi characters are identical to the Japanese oni in tourist marketing. However, the pursuit for dokkaebi’s authentic visual representation is less interesting and fruitful than the appreciation of the entire spectrum of dokkaebi images that have been created. Thus, scholars and stakeholders must not exclude the possibilities for a variety of potentials within the visual culture. The same sentiment applies to traditional art and craft. This study aims to contribute to a new visualization of the dokkaebi that embraces the possibilities of both folk craft and art, which continue to be uncovered by diverse and careful researchers in a still-developing field.

Keywords: Dokkaebi, post-colonial period, representation, tourist marketing

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

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Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

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Authors: Abigail Qian Zhou

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Since China has entered an era of mass tourism, there has been a fundamental change in the way Chinese people approach and perceive the image of other countries. With the advent of the new media era, social networking sites such as Sina Weibo have become a tool for many foreign governmental organizations to spread and promote their national image. Among them, the Japan National Tourism Organization (JNTO) was one of the first foreign official tourism agencies to register with Sina Weibo and actively implement communication activities. Due to historical and political reasons, cognition of Japan's national image by the Chinese has always been complicated and contradictory. However, since 2015, China has become the largest source of tourists visiting Japan. This clearly indicates that the broadening of Japan's national image in China has been effective and has value worthy of reference in promoting a positive Chinese perception of Japan and encouraging Japanese tourism. Within this context and using the method of content analysis in media studies through content mining software, this study analyzed how JNTO’s Sina Weibo accounts have constructed and spread Japan's national image. This study also summarized the characteristics of its content and form, and finally revealed the strategy of JNTO in building its international image. The findings of this study not only add a tourism-based perspective to traditional national image communications research, but also provide some reference for the effective international dissemination of national image in the future.

Keywords: national image, international communication, tourism, Japan, China

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Authors: Pooja Sharma, Renu Jain, Alka David

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The primary goal of this research is to comprehend the many features of visual merchandising (VM) and impulsive or instant purchasing behavior. It aims to explain the link between visual merchandising and customer purchasing behavior. The reviews were compiled from research articles, professional journal articles, and the opinions of many authors. It also discusses the impact of different internal and external VM elements on instant purchasing. The visual merchandising elements are divided into two sections: interior element (inside the display, spaces, and layout, fixtures, mannequins, attention-grabbing device) and outside element (outside display, space, and layout, fixture, mannequins, attention-grabbing device) (Window Display, Exterior signs, Marquees, Entrance, color, and texture). By focusing on selected clothing stores from the four markets of Bhopal city, we discovered that the exterior elements (window display, color, and texture) and interior elements (mannequins like dummies and fixtures such as lighting) have a significant positive impact on instant buying among the elements of Visual merchandising.

Keywords: instant purchase, visual merchandising, instant buying behavior, consumer behavior, window display, fixtures, mannequins, marquees

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Authors: Nour-Elhouda Lecheheb

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Destination image is one of the main factors that influence potential visitors' decision choice. This study aims to explore the pre-visit perception of prior British tourists and compare them to the actual projected images of the Algerian tourism suppliers. Semi-structured interviews are conducted with both prior British tourists to Algeria and the Algerian tourism suppliers in 2019. The findings of this study suggest how the Algerian tourism suppliers might benefit from understanding the perceived image of prior tourists to match tourists' expectations and better plan their projected images.

Keywords: Algeria, destination choice, destination image, perceived image, projected image

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Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Adnan A. Y. Mustafa

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Image matching is a fundamental problem that arises frequently in many aspects of robot and computer vision. It can become a time-consuming process when matching images to a database consisting of hundreds of images, especially if the images are big. One approach to reducing the time complexity of the matching process is to reduce the search space in a pre-matching stage, by simply removing dissimilar images quickly. The Probabilistic Matching Model for Binary Images (PMMBI) showed that dissimilarity detection between binary images can be accomplished quickly by random pixel mapping and is size invariant. The model is based on the gamma binary similarity distance that recognizes an image and its inverse as containing the same scene and hence considers them to be the same image. However, in many applications, an image and its inverse are not treated as being the same but rather dissimilar. In this paper, we present a comparative analysis of dissimilarity detection between PMMBI based on the gamma binary similarity distance and a modified PMMBI model based on a similarity distance that does distinguish between an image and its inverse as being dissimilar.

Keywords: binary image, dissimilarity detection, probabilistic matching model for binary images, image mapping

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Authors: Michael Zimba

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A novel set of features for copy-move image forgery, CMIF, detection method is proposed. The proposed set presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilised to extract robust features. The extracted features are shown to be invariant to additive noise, JPEG compression, and affine transformation. The proposed features can also be used in general object matching.

Keywords: virtual electrostatic field, features, affine transformation, copy-move image forgery

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Authors: Diego Luján Villarreal

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Retinal prosthetic devices aim to repair some vision in visual impairment patients by stimulating electrically neural cells in the visual system. In this study, the 3D linear electrode carrier is presented. A simulation framework was developed by placing the 3D carrier 1 mm away from the fovea center at the highest-density cell. Cell stimulation is verified in COMSOL Multiphysics by developing a 3D computational model which includes the relevant retinal interface elements and dynamics of the voltage-gated ionic channels. Current distribution resulting from low threshold amplitudes produces a small volume equivalent to the volume confined by individual cells at the highest-density cell using small-sized electrodes. Delicate retinal tissue is protected by excessive charge density

Keywords: retinal prosthetic devices, visual devices, retinal implants., visual prosthetic devices

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Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

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Authors: Ye Wang, Ickjai Lee

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Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, trajectories. This paper proposes three visual analytic approaches for higher order information of trajectory data sets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical information, topological, and directional information. Experimental results demonstrate the applicability and usefulness of proposed three approaches.

Keywords: visual analytics, higher order information, trajectory datasets, spatio-temporal data

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Authors: Pitigalage Chamath Chandira Peiris

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A widely researched domain in the field of image processing in recent times has been single image super-resolution, which tries to restore a high-resolution image from a single low-resolution image. Many more single image super-resolution efforts have been completed utilizing equally traditional and deep learning methodologies, as well as a variety of other methodologies. Deep learning-based super-resolution methods, in particular, have received significant interest. As of now, the most advanced image restoration approaches are based on convolutional neural networks; nevertheless, only a few efforts have been performed using Transformers, which have demonstrated excellent performance on high-level vision tasks. The effectiveness of CNN-based algorithms in image super-resolution has been impressive. However, these methods cannot completely capture the non-local features of the data. Enhancer is a simple yet powerful Transformer-based approach for enhancing the resolution of images. A method for single image super-resolution was developed in this study, which utilized an efficient and effective transformer design. This proposed architecture makes use of a locally enhanced window transformer block to alleviate the enormous computational load associated with non-overlapping window-based self-attention. Additionally, it incorporates depth-wise convolution in the feed-forward network to enhance its ability to capture local context. This study is assessed by comparing the results obtained for popular datasets to those obtained by other techniques in the domain.

Keywords: single image super resolution, computer vision, vision transformers, image restoration

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Authors: Soni Ariawan

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The study aims to explore the cultural diversity highlighted in EFL textbook for Senior High School grade 10 in Indonesia. The visual images are selected as the data and qualitatively analysed using content analysis. The reason to choose visual images because images are not always neutral and they might impact teaching and learning process. In the current study, cultural diversity aspects are focused on religion (Muslim, Protestant, Catholic, Hindu, Buddhist, Confucian), gender (male, female, unclear), ethnic (Melanesian, Austronesian, Foreigner) and socioeconomic (low, middle, high, undetermined) diversity as the theoretical framework. The four aspects of cultural diversity are sufficiently representative to draw a conclusion in investigating Indonesian culture representation in EFL textbook. The finding shows that cultural diversity is not proportionally reflected in the textbook, particularly in the visual images.

Keywords: EFL textbook, cultural diversity, visual images, Indonesia

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Authors: Jun Seung Woo, Shin Dong Ho

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The Image Captioning models with Attention technology have developed significantly compared to previous models, but it is still unsatisfactory in recognizing images. We perform an extensive search over seven interesting Convolutional Neural Networks(CNN) architectures to analyze the behavior of different models for image captioning. We compared seven different CNN Architectures, according to batch size, using on public benchmarks: MS-COCO datasets. In our experimental results, DenseNet and InceptionV3 got about 14% loss and about 160sec training time per epoch. It was the most satisfactory result among the seven CNN architectures after training 50 epochs on GPU.

Keywords: deep learning, image captioning, CNN architectures, densenet, inceptionV3

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Authors: Jacek Turski

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The visual space geometries are constructed in the Riemannian geometry framework from simulated iso-disparity conics in the horizontalvisual plane of the binocular system with the asymmetric eyes (AEs). For the eyes fixating at the abathic distance, which depends on the AE’s parameters, the iso-disparity conics are frontal straight lines in physical space. For allother fixations, the iso-disparity conics consist of families of the ellipses or hyperbolas depending on both the AE’s parameters and the bifoveal fixation. However, the iso-disparity conic’s arcs are perceived in the gaze direction asthe frontal lines and are referred to as visual geodesics. Thus, geometriesof physical and visual spaces are different. A simple postulate that combines simulated iso-disparity conics with basic anatomy od the human visual system gives the relative depth for the fixation at the abathic distance that establishes the Riemann matric tensor. The resulting geodesics are incomplete in the gaze direction and, therefore, give thefinite distances to the horizon that depend on the AE’s parameters. Moreover, the curvature vanishes in this eyes posture such that visual space is flat. For all other fixations, only the sign of the curvature canbe inferred from the global behavior of the simulated iso-disparity conics: the curvature is positive for the elliptic iso-disparity curves and negative for the hyperbolic iso-disparity curves.

Keywords: asymmetric eye model, iso-disparity conics, metric tensor, geodesics, curvature

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Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

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Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Ajish Sreedharan

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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. As encryption process is applied to the whole image in AES ,it is difficult to improve the efficiency. In this paper, wavelet decomposition is used to concentrate the main information of image to the low frequency part. Then, AES encryption is applied to the low frequency part. The high frequency parts are XORed with the encrypted low frequency part and a wavelet reconstruction is applied. Theoretical analysis and experimental results show that the proposed algorithm has high efficiency, and satisfied security suits for image data transmission.

Keywords: discrete wavelet transforms, AES, dynamic SBox

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Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

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Authors: Mostafa Jafari

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How the people continually create and recreate the six dimensional inter- sub-cultural relationships from the strategic point of view? Can they engineer and direct it toward creating a set of peaceful subcultures? This paper answers to these questions. Our mental images shape the quantity and quality of our relationships. The six dimensions of mental images are: my mental image about myself, your mental image about yourself, my mental image about you, your mental image about me, my imagination about your image about me and your imagination about my mental image about you. Strategic engineering is dynamically shaping these images and imaginations.Methodology: This survey, which is based on object and the relation between the variables, is explanatory, correlative and quantitative. The target community members are 90 educated people from universities. The data has been collected through questionnaire and interview and has been analyzed by descriptive statistical techniques and qualitative method. Results: Our findings show that engineering and deliberatly managing the process of inter- sub-cultural transactions in the national and global level can enable us to continually reform a peaceful set of learner sub-culturals toward recreate a peaceful unit global Home.

Keywords: strategic engineering, mental image, six dimensional mental images strategy , cultural literacy, radar technique

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Authors: Bahloul Amel

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The present study debates students’ perceptions of the use of technology in learning English as a Foreign Language. Its aim is to explore and understand students’ preparation and presentation of Posters, PowerPoint and Animated Videos by drawing attention to visual and oral elements. The data is collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. The themes emerged from the data, visual learning satisfaction in using information and communication technology, providing structure to oral presentation, learning from peers’ presentations, draw attention to using Posters, PowerPoint and Animated Videos as each supports visual learning and organization of thoughts in oral presentations.

Keywords: EFL, posters, PowerPoint presentations, Animated Videos, visual learning

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Aliana Leong, T. C. Huan

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The purpose of Nostalgic themed tourism product is becoming popular in many countries. This study intends to investigate the role of nostalgia in destination image, experiential value and their effect on subsequent behavioral intention. The survey used stratified sampling method to include respondents from all the nearby Asian regions. The sampling is based on the data of inbound tourists provided by the Statistics and Census Service (DSEC) of government of Macau. The questionnaire consisted of five sections of 5 point Likert scale questions: (1) nostalgia, (2) destination image both before and after experience, (3) expected value, (4) experiential value, and (5) future visit intention. Data was analysed with structural equation modelling. The result indicates that nostalgia plays an important part in forming destination image and experiential value before individual had a chance to experience the destination. The destination image and experiential value share a bidirectional causal relationship that eventually contributes to future visit intention. The study also discovered that while experiential value is more effective in generating destination image, the later contribute more to future visit intention. The research design measures destination image and experiential value before and after respondents had experience the destination. The distinction between destination image and expected/experiential value can be examined because the longitudinal design of research method. It also allows this study to observe how nostalgia translates to future visit intention.

Keywords: nostalgia, destination image, experiential value, future visit intention

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

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This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

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