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Introduction to EEG- and speech-based emotion recognition
by
Mehrotra, Suresh C.
,
Gawali, Bharti W.
,
Abhang, Priyanka A
in
Brain-computer interfaces
,
Electroencephalography
,
Emotions -- Research
2016
Introduction to EEG- and Speech-Based Emotion Recognition Methods examines the background, methods, and utility of using electroencephalograms (EEGs) to detect and recognize different emotions.By incorporating these methods in brain-computer interface (BCI), we can achieve more natural, efficient communication between humans and computers.
Research methods in human-computer interaction
by
Lazar, Jonathan
,
Hochheiser, Harry
,
Feng, Jinjuan Heidi
in
Human-computer interaction -- Research
2017
Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods.Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University.
Artificial Intelligence in Radiation Therapy
2023
This textbook covers a basis of mathematical algorithm in artificial intelligence and clinical adaptation and contribution of AI in radiotherapy. More experienced practitioners and researchers and members of medical physics communities, such as AAPM, ASTRO, and ESTRO, would find this book extremely useful.
Practical Industrial Internet of Things Security
by
Bhattacharjee, Sravani
in
Computer networks
,
COMPUTERS / Computer Architecture
,
Internet of things
2018,2024
This book provides you with a comprehensive understanding of Industrial IoT security; and practical methodologies to implement safe, resilient cyber-physical systems. It will help you develop a strong foundation and deeper insights on the entire gamut of securing connected industries, from the edge to the cloud.
Advanced deep learning with TensorFlow 2 and Keras : apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more
2020,2024
A second edition of the bestselling guide to exploring and mastering deep learning with Keras, updated to include TensorFlow 2.x with new chapters on object detection, semantic segmentation, and unsupervised learning using mutual information.