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Deep Features Based Hierarchical Classification Scheme For Face Recognition In Heterogeneous Environments
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Book Synopsis Deep Features Based Hierarchical Classification Scheme for Face Recognition in Heterogeneous Environments by : Neeru Narang
Download or read book Deep Features Based Hierarchical Classification Scheme for Face Recognition in Heterogeneous Environments written by Neeru Narang and published by . This book was released on 2017 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Face Image Analysis with Convolutional Neural Networks by : Stefan Duffner
Download or read book Face Image Analysis with Convolutional Neural Networks written by Stefan Duffner and published by GRIN Verlag. This book was released on 2009-08-12 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doctoral Thesis / Dissertation from the year 2008 in the subject Computer Science - Applied, grade: 1, University of Freiburg (Lehrstuhl für Mustererkennung und Bildverarbeitung), language: English, abstract: In this work, we present the problem of automatic appearance-based facial analysis with machine learning techniques and describe common specific sub-problems like face detection, facial feature detection and face recognition which are the crucial parts of many applications in the context of indexation, surveillance, access-control or human-computer interaction. To tackle this problem, we particularly focus on a technique called Convolutional Neural Network (CNN) which is inspired by biological evidence found in the visual cortex of mammalian brains and which has already been applied to many different classi fication problems. Existing CNN-based methods, like the face detection system proposed by Garcia and Delakis, show that this can be a very effective, efficient and robust approach to non-linear image processing tasks. An important step in many automatic facial analysis applications, e.g. face recognition, is face alignment which tries to translate, scale and rotate the face image such that specific facial features are roughly at predefined positions in the image. We propose an efficient approach to this problem using CNNs and experimentally show its very good performance on difficult test images. We further present a CNN-based method for automatic facial feature detection. The proposed system employs a hierarchical procedure which first roughly localizes the eyes, the nose and the mouth and then refines the result by detecting 10 different facial feature points. The detection rate of this method is 96% for the AR database and 87% for the BioID database tolerating an error of 10% of the inter-ocular distance. Finally, we propose a novel face recognition approach based on a specific CNN architecture learning a non-linear mapping of the image space into a lower-dimensional sub-space where the different classes are more easily separable. We applied this method to several public face databases and obtained better recognition rates than with classical face recognition approaches based on PCA or LDA. We also present a CNN-based method for the binary classification problem of gender recognition with face images and achieve a state-of-the-art accuracy. The results presented in this work show that CNNs perform very well on various facial image processing tasks, such as face alignment, facial feature detection and face recognition and clearly demonstrate that the CNN technique is a versatile, efficient and robust approach for facial image analysis.
Book Synopsis Face Recognition by : S. Ramakrishnan
Download or read book Face Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2016-07-06 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition has gained significant attention due to the rapid explosion of internet- and mobile-based applications. Among the various pattern recognition applications, face recognition is always being the center of attraction. With so much of unlabeled face images being captured and made available on internet (particularly on social media), conventional supervised means of classifying face images become challenging. This clearly warrants for semi-supervised classification and subspace projection. Another important concern in face recognition system is the proper and stringent evaluation of its capability. This book is edited keeping all these factors in mind. This book is composed of five chapters covering introduction, overview, semi-supervised classification, subspace projection, and evaluation techniques.
Book Synopsis Local Binary Pattern Network by : Meng Xi
Download or read book Local Binary Pattern Network written by Meng Xi and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Deep learning is well known as a method to extract hierarchical representations of data. This method has been widely implemented in many fields, including image classification, speech recognition, natural language processing, etc. Over the past decade, deep learning has made a great progress in solving face recognition problems due to its effectiveness. In this thesis a novel deep learning multilayer hierarchy based methodology, named Local Binary Pattern Network (LBPNet), is proposed. Unlike the shallow LBP method, LBPNet performs multi-scale analysis and gains high-level representations from low-level overlapped features in a systematic manner. The LBPNet deep learning network is generated by retaining the topology of Convolutional Neural Network (CNN) and replacing its trainable kernel with the off-the-shelf computer vision descriptor, the LBP descriptor. This enables LBPNet to achieve a high recognition accuracy without requiring costly model learning approach on massive data. LBPNet progressively extracts features from input images from test and training data through multiple processing layers, pairwisely measures the similarity of extracted features in regional level, and then performs the classification based on the aggregated similarity values. Through extensive numerical experiments using the popular benchmarks (i.e., FERET, LFW and YTF), LBPNet has shown the promising results. Its results out-perform (on FERET) or are comparable (on LFW and FERET) to other methods in the same categories, which are single descriptor based unsupervised learning methods on FERET and LFW, and single descriptor based supervise learning methods with image-restricted no outside data settings on LFW and YTF, respectively."--Leaves i-ii.
Download or read book Face Recognition written by Haidong Wang and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Machine Learning for Face, Emotion, and Pain Recognition by : Gholamreza Anbarjafari
Download or read book Machine Learning for Face, Emotion, and Pain Recognition written by Gholamreza Anbarjafari and published by . This book was released on 2018 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Spotlight explains how to build an automated system for face, emotion, and pain recognition. These steps include pre-processing, face detection and segmentation, feature extraction, and finally and most importantly, recognition to classify features and show the accuracy of the system. State-of-the-art algorithms are used to describe all possible solutions of each step. Pre-processing involves algorithms to reduce noise and improve the illumination of images. For face detection and segmentation, several approaches are described to detect a face in images: Viola-Jones, color-based approaches, histogram-based approaches, and morphological operation. Local binary patterns, edge detectors, wavelets, discrete Cosine transformation, Gabor filters, and fuzzified features are used for feature extraction. The last step includes three approaches for recognition: classification techniques (with a special focus on deep learning), statistical modeling, and distance/similarity measures.
Book Synopsis Machine Learning for Face, Emotion, and Pain Recognition by : Gholamreza Anbarjafari
Download or read book Machine Learning for Face, Emotion, and Pain Recognition written by Gholamreza Anbarjafari and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This Spotlight explains how to build an automated system for face, emotion, and pain recognition. These steps include pre-processing, face detection and segmentation, feature extraction, and finally and most importantly, recognition to classify features and show the accuracy of the system. State-of-the-art algorithms are used to describe all possible solutions of each step. Pre-processing involves algorithms to reduce noise and improve the illumination of images. For face detection and segmentation, several approaches are described to detect a face in images: Viola-Jones, color-based approaches, histogram-based approaches, and morphological operation. Local binary patterns, edge detectors, wavelets, discrete Cosine transformation, Gabor filters, and fuzzified features are used for feature extraction. The last step includes three approaches for recognition: classification techniques (with a special focus on deep learning), statistical modeling, and distance/similarity measures.
Book Synopsis China’s e-Science Blue Book 2020 by : Chinese Academy of Sciences
Download or read book China’s e-Science Blue Book 2020 written by Chinese Academy of Sciences and published by Springer Nature. This book was released on 2021-01-08 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: “China’s e-Science Blue Book 2020” has been jointly compiled by the Chinese Academy of Sciences, Cyberspace Administration of China, Ministry of Education of the PRC, Ministry of Science and Technology of the PRC, China Association for Science and Technology, Chinese Academy of Social Sciences, National Natural Science Foundation of China and the Chinese Academy of Agricultural Sciences. It was focusing on the new situation, new progress and new achievements of China's e-Scientific in the past two years. During the “13th Five-Year Plan” period, Chinese scholars make full use of advanced information technology to carry out scientific research work, and have achieved a series of major scientific and technological achievements. This book has collected 28 research reports about China’s e-Science application in the past two years to introduce the application in the frontier research of science and technology, the progress of e-Science in major projects and the achievements of informatization in interdisciplinary. As such it provides a valuable reference resource for researchers and students in this area and promotes further e-Science research.
Book Synopsis Hierarchical Neural Networks for Image Interpretation by : Sven Behnke
Download or read book Hierarchical Neural Networks for Image Interpretation written by Sven Behnke and published by Springer. This book was released on 2003-11-18 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.
Book Synopsis Green Communications and Networking by : F. Richard Yu
Download or read book Green Communications and Networking written by F. Richard Yu and published by CRC Press. This book was released on 2016-04-19 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Green Communications and Networking introduces novel solutions that can bring about significant reductions in energy consumption in the information and communication technology (ICT) industry-as well as other industries, including electric power. Containing the contributions of leading experts in the field, it examines the latest research advances
Book Synopsis Advances in Control Power Systems and Emerging Technologies by : Mohamed Bendaoud
Download or read book Advances in Control Power Systems and Emerging Technologies written by Mohamed Bendaoud and published by Springer Nature. This book was released on with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applications of Small Unmanned Aircraft Systems by : J.B. Sharma
Download or read book Applications of Small Unmanned Aircraft Systems written by J.B. Sharma and published by CRC Press. This book was released on 2019-10-18 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in high spatial resolution mapping capabilities and the new rules established by the Federal Aviation Administration in the United States for the operation of Small Unmanned Aircraft Systems (sUAS) have provided new opportunities to acquire aerial data at a lower cost and more safely versus other methods. A similar opening of the skies for sUAS applications is being allowed in countries across the world. Also, sUAS can access hazardous or inaccessible areas during disaster events and provide rapid response when needed. Applications of Small Unmanned Aircraft systems: Best Practices and Case Studies is the first book that brings together the best practices of sUAS applied to a broad range of issues in high spatial resolution mapping projects. Very few sUAS pilots have the knowledge of how the collected imagery is processed into value added mapping products that have commercial and/or academic import. Since the field of sUAS applications is just a few years old, this book covers the need for a compendium of case studies to guide the planning, data collection, and most importantly data processing and map error issues, with the range of sensors available to the user community. Written by experienced academics and professionals, this book serves as a guide on how to formulate sUAS based projects, from choice of a sUAS, flight planning for a particular application, sensors and data acquisition, data processing software, mapping software and use of the high spatial resolution maps produced for particular types of geospatial modeling. Features: Focus on sUAS based data acquisition and processing into map products Broad range of case studies by highly experienced academics Practical guidance on sUAS hardware, sensors, and software utilized Compilation of workflow insights from expert professors and professionals Relevant to academia, government, and industry Positional and thematic map accuracy, UAS curriculum development and workflow replicability issues This book would be an excellent text for upper-level undergraduate to graduate level sUAS mapping application courses. It is also invaluable as a reference for educators designing sUAS based curriculum as well as for potential sUAS users to assess the scope of mapping projects that can be done with this technology.
Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
Book Synopsis Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods by : Kemal Polat
Download or read book Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods written by Kemal Polat and published by Elsevier. This book was released on 2023-04-30 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important Includes novel methodologies, datasets, design and simulation examples
Book Synopsis Hyperspectral Image Analysis by : Saurabh Prasad
Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Book Synopsis Face Recognition Technologies by : Douglas Yeung
Download or read book Face Recognition Technologies written by Douglas Yeung and published by Rand Corporation. This book was released on 2020-05-15 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Face recognition technologies (FRTs) have many practical security-related purposes, but advocacy groups and individuals have expressed apprehensions about their use. This report highlights the high-level privacy and bias implications of FRT systems. The authors propose a heuristic with two dimensions -- consent status and comparison type -- to help determine a proposed FRT's level of privacy and accuracy. They also identify privacy and bias concerns.
Book Synopsis Symmetry-Adapted Machine Learning for Information Security by : James (Jong Hyuk) Park
Download or read book Symmetry-Adapted Machine Learning for Information Security written by James (Jong Hyuk) Park and published by MDPI. This book was released on 2020-12-15 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis.
