Explainable Ai Applications For Human Behavior Analysis

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Explainable Ai Applications For Human Behavior Analysis

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Author : Paramasivan, P.
language : en
Publisher: IGI Global
Release Date : 2024-05-20

Explainable Ai Applications For Human Behavior Analysis written by Paramasivan, P. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-20 with Computers categories.

In the field of computer vision research, the study of human behavior is a formidable challenge. The diverse applications of this field, from video surveillance for crowd analysis to healthcare diagnostics, have drawn increasing attention. However, a significant problem persists – the sacrifice of transparency for the sake of predictive accuracy in Artificial Intelligence (AI) solutions. These AI systems often operate as enigmatic black boxes, seemingly conjuring decisions from vast datasets with little to no explanation. The need for clarity and accountability in AI decision-making is paramount as our reliance on these systems continues to grow. Explainable AI Applications for Human Behavior Analysis embarks on a mission to harness AI's innate capability to elucidate upon its own decision-making processes. By focusing on facial expressions, gestures, and body movements, we delve into uncharted territories of research, offering novel methodologies, databases, benchmarks, and algorithms for the analysis of human behavior in natural settings. Geared toward academic scholars, this book compiles the expertise of leading researchers in the field, making it accessible to readers of all educational backgrounds.

Explainable Ai Interpreting Explaining And Visualizing Deep Learning

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Author : Wojciech Samek
language : en
Publisher: Springer Nature
Release Date : 2019-09-10

Explainable Ai Interpreting Explaining And Visualizing Deep Learning written by Wojciech Samek and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-10 with Computers categories.

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.

Explainable Ai With Python

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Author : Antonio Di Cecco
language : en
Publisher: Springer Nature
Release Date : 2025-08-04

Explainable Ai With Python written by Antonio Di Cecco and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-04 with Computers categories.

This comprehensive book on Explainable Artificial Intelligence has been updated and expanded to reflect the latest advancements in the field of XAI, enriching the existing literature with new research, case studies, and practical techniques. The Second Edition expands on its predecessor by addressing advancements in AI, including large language models and multimodal systems that integrate text, visual, auditory, and sensor data. It emphasizes making complex systems interpretable without sacrificing performance and provides an enhanced focus on additive models for improved interpretability. Balancing technical rigor with accessibility, the book combines theory and practical application to equip readers with the skills needed to apply explainable AI (XAI) methods effectively in real-world contexts. Features: Expansion of the "Intrinsic Explainable Models" chapter to delve deeper into generalized additive models and other intrinsic techniques, enriching the chapter with new examples and use cases for a better understanding of intrinsic XAI models. Further details in "Model-Agnostic Methods for XAI" focused on how explanations differ between the training set and the test set, including a new model to illustrate these differences more clearly and effectively. New section in "Making Science with Machine Learning and XAI" presenting a visual approach to learning the basic functions in XAI, making the concept more accessible to readers through an interactive and engaging interface. Revision in "Adversarial Machine Learning and Explainability" that includes a code review to enhance understanding and effectiveness of the concepts discussed, ensuring that code examples are up-to-date and optimized for current best practices. New chapter on "Generative Models and Large Language Models (LLM)" chapter dedicated to generative models and large language models, exploring their role in XAI and how they can be used to create richer, more interactive explanations. This chapter also covers the explainability of transformer models and privacy through generative models. New "Artificial General Intelligence and XAI" mini-chapter dedicated to exploring the implications of Artificial General Intelligence (AGI) for XAI, discussing how advancements towards AGI systems influence strategies and methodologies for XAI. Enhancements in "Explaining Deep Learning Models" features new methodologies in explaining deep learning models, further enriching the chapter with cutting-edge techniques and insights for deeper understanding.

Conference Record For 1992 Fifth Conference On Human Factors And Power Plants

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Author : E. W. Hagen
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1992

Conference Record For 1992 Fifth Conference On Human Factors And Power Plants written by E. W. Hagen and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Science categories.

Electro Conference Record

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Author :
language : en
Publisher:
Release Date : 1988

Electro Conference Record written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.

Explainable Artificial Intelligence A Practical Guide

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Author : Parikshit Narendra Mahalle
language : en
Publisher: CRC Press
Release Date : 2024-12-02

Explainable Artificial Intelligence A Practical Guide written by Parikshit Narendra Mahalle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Computers categories.

This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI. Technical topics discussed in the book include: Explainable AI overview Understanding black box models Techniques for model interpretability Practical applications of XAI Future trends and challenges in XAI

Mathematical Reviews

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Author :
language : en
Publisher:
Release Date : 1995

Mathematical Reviews written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Mathematics categories.

Encyclopedia Of Physical Science And Technology

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Author :
language : en
Publisher:
Release Date : 2002

Encyclopedia Of Physical Science And Technology written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Physical sciences categories.

Of the Encyclopedia of Physical Science and Technology: Has been completely updated with no less than 90% revised material and 50% new content throughout the volumes Presents eighteen volumes, nearly 800 authoritative articles and 14,500 pages Is lavishly illustrated with over 7,000 photographs, illustrations and tables Presents an increased emphasis on the hottest topics such as information processing, environmental science, biotechnology and biomedicine Includes a final Index Volume containing Thematic, Relational and Subject indexes.

Explainable Interpretable And Transparent Ai Systems

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Author : B. K. Tripathy
language : en
Publisher: CRC Press
Release Date : 2024-08-23

Explainable Interpretable And Transparent Ai Systems written by B. K. Tripathy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-23 with Technology & Engineering categories.

Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains. Features: Presents a clear focus on the application of explainable AI systems while tackling important issues of “interpretability” and “transparency”. Reviews adept handling with respect to existing software and evaluation issues of interpretability. Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression. Focuses on interpreting black box models like feature importance and accumulated local effects. Discusses capabilities of explainability and interpretability. This book is aimed at graduate students and professionals in computer engineering and networking communications.

On The Human In Human Artificial Intelligence Interaction

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Author : Stefano Triberti
language : en
Publisher: Frontiers Media SA
Release Date : 2022-02-10

On The Human In Human Artificial Intelligence Interaction written by Stefano Triberti and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-10 with Science categories.