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This book provides an in-depth investigation on the psychological phenomenon "reactance“ in the context of Human-Computer Interaction... Læs mere
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This book focuses on enabling mobile robots to recognize scenes in indoor environments, in order to allow them to determine which actions are appropriate at which points in time.
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This book addresses Assistive Augmentation, highlighting the design and development of assistive technologies, user interfaces, and interactions that seamlessly integrate with a... Læs mere
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This book highlights the methods and applications for roadside video data analysis, with a particular focus on the use of deep learning to solve roadside video data segmentation and classification problems.
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This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance... Læs mere
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This book shows how mathematics, computer science and science can be usefully and seamlessly intertwined. It introduces specialized data for emotional content, which allows a brain model to be built using MatLab tools, and also highlights a simple model of cognitive dysfunction.
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This book provides a self-study program on how mathematics, computer science and science can be usefully and seamlessly intertwined. Learning to use ideas from mathematics and computation is essential for understanding approaches to cognitive and biological science.
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This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly... Læs mere
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It is a follow-up to the first two volumes on mathematics for cognitive scientists, and includes the mathematics and computational tools needed to understand how to compute the terms in the Fourier series expansions that solve the cable equation.
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This book constitutes the referred proceedings of the 17th International... Læs mere
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Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation.
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The book discusses Explainable (XAI) and Responsive Artificial Intelligence (RAI) for biomedical and healthcare applications. The book explains both positive as well as negative findings obtained by explainable AI techniques.