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Machine Learning Systems for Multimodal Affect Recognition

focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise;

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Challenges and Trends in Multimodal Fall Detection for Healthcare

statistics for automated, human fall recognition systems and related topics using data fusion. It includes theory and coding implementations to help;

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Physiological Computing Systems

, machine learning applied to diabetes and hypertension, tangible biofeedback technologies, multimodal sensor data fusion, and deep learning for;

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New Perspectives on Affect and Learning Technologies

processes - Multimodal Human Computer Interfaces, with a focus on affect recognition and synthesis - Recent advances in affect-sensitive Intelligent;

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Multimodal Interactive Handwritten Text Transcription

This book presents an interactive multimodal approach for efficient transcription of handwritten text images. This approach, rather than;

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Machine Learning for Speaker Recognition

This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;

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Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held;

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MPRSS 2016

recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition;

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Handbook of Multibiometrics

Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial;

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Handbook of Multibiometrics

Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial;

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The Paradigm Shift to Multimodality in Contemporary Computer Interfaces

is growing rapidly in areas like multimodal data analytics, affect recognition, accessible interfaces, embedded and robotic interfaces, machine;

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Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the;

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Symbolic Visual Learning

Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning.;

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Advances in Biometrics for Secure Human Authentication and Recognition

used for human authentication and recognition. Examining the full range of biometrics solutions, including unimodal and multimodal;

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Evolutionary Synthesis of Pattern Recognition Systems

in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data;

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Medical Content-Based Retrieval for Clinical Decision Support

, MRI, CT, echo videos, time series data), machine learning of disease correlations in visual or multimodal data, algorithms for indexing and;

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

environments. After an introduction, the editors organize the book into four main parts on sentiment, affect and emotion analytics for big multimodal;

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Intelligent Learning Systems

Intelligent (machine) learning is a subfield of artificial intelligence and it originates from the researches in the pattern recognition;

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The Oxford Handbook of Affective Computing

, cognitive, social, media, and brain sciences. Section Two focuses on affect detection or affect recognition, which is one of the most commonly;

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Machine Learning for Networking

submissions. They present and discuss new trends in deep and reinforcement learning, pattern recognition and classification for networks, machine;

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Machine Learning The New AI

systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product;

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Machine Vision Inspection Systems

, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry;

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Machine Learning for Networking: First International Conference, Mln 2018, Paris, France, November 27-29, 2018, Revised Selected Papers

This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN;

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Advances in Computational Intelligence

forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface;

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Advances in Computational Intelligence

forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface;

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Multimodal Analyses enabling Artificial Agents in Human Machine Interaction

This book constitutes the thoroughly refereed post-workshop proceedings of the Second Workshop on Multimodal Analyses Enabling Artificial;

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Dynamic Vision

impact on computer vision and machine learning research at large. It raises many challenging issues and provides a good vehicle for examining;

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