This 2nd Edition, based on the successful 2016 textbook, has been updated and expanded to cover 3rd generation Computer Vision and AI as it supersedes historical visual computing methods, providing a comprehensive survey of essential topics and methods in Computer Vision.
This book proposes practical application paradigms for deep neural networks, aiming to establish best practices for their real-world implementation.
This book delves into the transformative potential of artificial intelligence (AI) and machine learning (ML) as game-changers in diagnosing and managing of neurodisorder conditions. It covers a wide array of methodologies, algorithms, and applications in depth.
The book will be related to applied machine learning and deep learning in the field of sensing, vision and sensor-based applications.
The book will be related to applied machine learning and deep learning in the field of sensing, vision and sensor-based applications.
It will cover action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, healthcare, dementia, nursing, Parkinson’s disease, and related areas.