Advances In Pattern Analysis And Intelligent Sensing - Böcker
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2 produkter
2 produkter
Del 1 - Advances In Pattern Analysis And Intelligent Sensing
Advanced Randomized Neural Networks For Pattern Analysis
Inbunden, Engelska, 2025
1 817 kr
Skickas inom 3-6 vardagar
This book is the culmination of our research in the recent decade on randomized neural networks with data-dependent supervision mechanisms. Traditional randomized neural networks mainly focused on constructing various deep neural networks with data independent random weights, ignoring the impact of the number of nodes and scope of parameters on the universal approximation property (UAP) of randomized neural networks. Comprising of 15 chapters, Advanced Randomized Neural Networks for Pattern Analysis introduces systematic solutions for advanced data-dependent stochastic configuration networks, namely algorithms that assign random parameters and construct network structures incrementally. The book is segmented into three major sections — neural networks optimization, robust data analysis, and deep fusion learning — that feature the successful performance of advanced randomized neural networks in various pattern analysis problems. We anticipate that both researchers and engineers in the field of artificial neural networks, particularly pattern recognition and medical diagnosis, will find this book and the associated algorithms useful, and we hope that anyone with an interest in the related research field will find the book enjoyable and informative.
Del 2 - Advances In Pattern Analysis And Intelligent Sensing
Advanced Medical Biometrics
Inbunden, Engelska, 2026
1 817 kr
Skickas inom 3-6 vardagar
In brief, this book provides the advanced sensing technologies including multi-sensor collaborative sensing for pulse signal acquisition, sensor array design for breath odor perception, and voice signal acquisition. Besides, this book summarizes the advances about pulse feature extraction with improved Gabor function, odor feature extraction based on de-convolution methods. This book also presents the latest recognition methods including evolutionary ensemble model to handle the imbalance problem, multi-feature complementary methods for face image, tongue images, and pulse analysis. Multi-modal hybrid fusion and self-adaptive score fusion for disease classification are proposed and proved effective for medical biometrics.Medical biometrics achieves disease detection and health monitor by sensing and recognizing multi-modal body surface information. It is believed that body surface information, e.g., face, tongue, breath odor, voice, and wrist pulse, is one of the most important biometric features that contains rich pathological information and can be used for health assessments or disease detection. Focusing on the latest progresses in medical biometrics, this book systematically presents advanced signal acquisition techniques, feature extraction methods, and recognition algorithms.Both researchers and engineers in pattern recognition and medical diagnosis will benefit from this book as it offers comprehensive understanding of the advanced signal acquisition techniques, related feature extraction methods, and state-of-the-art analysis methods.