Interpretable Deep Learning Based Approach For The Gait Recognition PDF Download
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| Author | : Nelson Hebert Minaya (Graduate student) |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 2021 |
| Genre | : Biometric identification |
| ISBN | : |
Download Interpretable Deep Learning-based Approach for the Gait Recognition Book in PDF, ePub and Kindle
Abstract: Human gait is a unique behavioral characteristic that can be used to recognize individuals. In recent years, the capture of gait information has become a common practice due to the advancement and accessibility of wearable devices that allow to collect it as continuous time-series. Recognizing people by processing this type of gait data has become a topic of research that looks for methods with enough high accuracy that would enable the use of gait for biometric identification. This work addresses the problem of user identification and recognition from collected multi-modal time-series gait information. The recognition problem has two different settings: the first one is closed-set recognition, whereby all testing classes are known at the time of training, and the other one is open-set recognition where unknown classes that were not in the training phase can emerge during testing. This work addresses both settings by proposing frameworks for each one. The inputs for the proposed frameworks are unit steps obtained by segmenting the multi-modal time series collected from individuals wearing a smart insole device.
| Author | : James Eric Mason |
| Publisher | : Springer |
| Total Pages | : 247 |
| Release | : 2016-02-04 |
| Genre | : Technology & Engineering |
| ISBN | : 3319290886 |
Download Machine Learning Techniques for Gait Biometric Recognition Book in PDF, ePub and Kindle
This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition · provides detailed discussions of key research challenges and open research issues in gait biometrics recognition · compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear
| Author | : Matteo Zago |
| Publisher | : Frontiers Media SA |
| Total Pages | : 328 |
| Release | : 2021-03-04 |
| Genre | : Science |
| ISBN | : 2889665615 |
Download Machine Learning Approaches to Human Movement Analysis Book in PDF, ePub and Kindle
| Author | : Nagender Kumar Suryadevara |
| Publisher | : Apress |
| Total Pages | : 182 |
| Release | : 2021-04-02 |
| Genre | : Computers |
| ISBN | : 9781484268421 |
Download Beginning Machine Learning in the Browser Book in PDF, ePub and Kindle
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental coding ideas. Using JavaScript programming features along with standard libraries, you'll first learn to design and develop interactive graphics applications. Then move further into neural systems and human pose estimation strategies. For training and deploying your ML models in the browser, TensorFlow.js libraries will be emphasized. After conquering the fundamentals, you'll dig into the wilderness of ML. Employ the ML and Processing (P5) libraries for Human Gait analysis. Building up Gait recognition with themes, you'll come to understand a variety of ML implementation issues. For example, you’ll learn about the classification of normal and abnormal Gait patterns. With Beginning Machine Learning in the Browser, you’ll be on your way to becoming an experienced Machine Learning developer. What You’ll Learn Work with ML models, calculations, and information gathering Implement TensorFlow.js libraries for ML models Perform Human Gait Analysis using ML techniques in the browser Who This Book Is For Computer science students and research scholars, and novice programmers/web developers in the domain of Internet Technologies
| Author | : Thomas Moeslund |
| Publisher | : MDPI |
| Total Pages | : 300 |
| Release | : 2020-06-17 |
| Genre | : Technology & Engineering |
| ISBN | : 3039362283 |
Download Statistical Machine Learning for Human Behaviour Analysis Book in PDF, ePub and Kindle
This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.
| Author | : Simone Tassani |
| Publisher | : Frontiers Media SA |
| Total Pages | : 120 |
| Release | : 2024-06-06 |
| Genre | : Technology & Engineering |
| ISBN | : 283255010X |
Download Cross-Disciplinary Approaches to Characterize Gait and Posture Disturbances in Aging and Related Diseases, volume II Book in PDF, ePub and Kindle
Aging introduces disturbances to the gait and posture of individuals. Such alterations can originate or result from a wide range of causes making it challenging to understand when modifications are related to pathological or physiological causes. Many disciplines come together to perform this kind of analysis (e.g. computational and experimental mechanics, image processing, medicine, biology, physiology, machine learning, and data science). Gait analysis is particularly sensitive to the interactions of different disciplines. This technique allows the study of human movements, but only through a multidisciplinary approach, it is possible to infer relations of causation. Narrow studies focusing on specific techniques are important to develop the fundamental tools required to study movement. In recent years, significant methodological advancements have been independently made in these fields. However, to cross the borders of current science and develop consistent results any new study needs to set interdisciplinary goals. An inclusive approach merging multiple aspects would be key in targeting pharmacological or rehabilitation interventions and improving patient care as a whole.
| Author | : Hiroshi Ishikawa |
| Publisher | : Springer Nature |
| Total Pages | : 757 |
| Release | : 2021-02-24 |
| Genre | : Computers |
| ISBN | : 3030695352 |
Download Computer Vision – ACCV 2020 Book in PDF, ePub and Kindle
The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.
| Author | : Harish Garg |
| Publisher | : Elsevier |
| Total Pages | : 402 |
| Release | : 2023-07-20 |
| Genre | : Computers |
| ISBN | : 0443194149 |
Download Deep Learning in Personalized Healthcare and Decision Support Book in PDF, ePub and Kindle
Deep Learning in Personalized Healthcare and Decision Support discusses the potential of deep learning technologies in the healthcare sector. The book covers the application of deep learning tools and techniques in diverse areas of healthcare, such as medical image classification, telemedicine, clinical decision support system, clinical trials, electronic health records, precision medication, Parkinson disease detection, genomics, and drug discovery. In addition, it discusses the use of DL for fraud detection and internet of things. This is a valuable resource for researchers, graduate students and healthcare professionals who are interested in learning more about deep learning applied to the healthcare sector. Although there is an increasing interest by clinicians and healthcare workers, they still lack enough knowledge to efficiently choose and make use of technologies currently available. This book fills that knowledge gap by bringing together experts from technology and clinical fields to cover the topics in depth. Discusses the application of deep learning in several areas of healthcare, including clinical trials, telemedicine and health records management Brings together experts in the intersection of deep learning, medicine, healthcare and programming to cover topics in an interdisciplinary way Uncovers the stakes and possibilities involved in realizing personalized healthcare services through efficient and effective deep learning technologies
| Author | : Kohei Arai |
| Publisher | : Springer Nature |
| Total Pages | : 1184 |
| Release | : 2021-07-12 |
| Genre | : Technology & Engineering |
| ISBN | : 3030801195 |
Download Intelligent Computing Book in PDF, ePub and Kindle
This book is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2021 held on 15-16 July 2021. Computing 2021 attracted a total of 638 submissions which underwent a double-blind peer review process. Of those 638 submissions, 235 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this volume interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications is a trigger for further related research and technology improvements in this important subject.
| Author | : Wojciech Samek |
| Publisher | : Springer Nature |
| Total Pages | : 435 |
| Release | : 2019-09-10 |
| Genre | : Computers |
| ISBN | : 3030289540 |
Download Explainable AI: Interpreting, Explaining and Visualizing Deep Learning Book in PDF, ePub and Kindle
The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.
