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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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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Condizione: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc. Codice articolo 00084536175
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