Deep Learning Applications of Short-Range Radars - Hardcover

Avik Santra; Souvik Hazra

9781630817466: Deep Learning Applications of Short-Range Radars

Hardcover

ISBN 10: 1630817465 ISBN 13: 9781630817466

Publisher: Artech House, 2020

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This exciting new resource covers various emerging applications of short range radars, including people counting and tracking, gesture sensing, human activity recognition, air-drawing, material classification, object classification, vital sensing by extracting features such as range-Doppler Images (RDI), range-cross range images, Doppler Spectrogram or directly feeding raw ADC data to the classifiers. The book also presents how deep learning architectures are replacing conventional radar signal processing pipelines enabling new applications and results. It describes how deep convolutional neural networks (DCNN), long-short term memory (LSTM), feedforward networks, regularization, optimization algorithms, connectionist This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book covers applications ranging from industrial, consumer space to emerging automotive applications. The book presents several human-machine interface (HMI) applications, such as gesture recognition and sensing, human activity classification, air-writing, material classification, vital sensing, people sensing, people counting, people localization and in-cabin automotive occupancy and smart trunk opening. The underpinnings of deep learning are explored, outlining the history of neural networks and the optimization algorithms to train them. Modern deep convolutional neural network (DCNN), popular DCNN architectures for computer vision and their features are also introduced. The book presents other deep learning architectures, such as long-short term memory (LSTM), auto-encoders, variational auto-encoders (VAE), and generative adversarial networks (GAN). The application of human activity recognition as well as the application of air-writing using a network of short-range radars are outlined. This book demonstrates and highlights how deep learning is enabling several advanced industrial, consumer and in-cabin applications of short-range radars, which weren't otherwise possible. It illustrates various advanced applications, their respective challenges, and how they are been addressed using different deep learning architectures and algorithms.

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About the Author

Avik Santra is a senior staff algorithm expert engineer at Infineon Technologies AG. He received an M.E. in signal processing from the Indian Institute of Science, Bengaluru. He is a Senior Member of IEEE. He has filed over 40 patents and has published over 25 research papers related to various topics of radar waveform design, radar signal processing, and radar machine/deep learning. Souvik Hazra is an AI engineering consultant at Infineon Technologies AG. He recieved a M.S. in data science and engineering from EURECOM & IMT, France. He has filed 5 patents and has published over 10 research articles on machine learning and deep learning topics.

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