Synopsis
"This exciting resource identifies technical challenges, benefits, and directions of Deep Learning (DL) based object classification using radar data (i.e., Synthetic Aperture Radar / SAR and High range resolution Radar / HRR data). An overview of machine learning (ML) theory to include a history, background primer, and example and performance of ML algorithm (i.e., DL method) on video imagery is provided. Radar data with issues of collection, application, and examples for SAR/HRR data and communication signals analysis is also discussed. Practical considerations of deploying such techniques, including performance evaluation, hardware issues, and the future unresolved issues are presented."--Amazon.com
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Deep Learning for Radar and Communications Automatic Target Recognition
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Artech House Publishers, 2020
ISBN 10: 163081637X
ISBN 13: 9781630816377
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Modern Machine Learning Algorithms for Radar and Communications (Hardcover)
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Artech House Publishers, Norwood, 2020
ISBN 10: 163081637X
ISBN 13: 9781630816377
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Hardcover. Condition: new. Hardcover. This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation.It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues. This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781630816377
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Deep Learning for Radar and Communications Automatic Target Recognition
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Deep Learning for Radar and Communications Automatic Target Recognition
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Deep Learning for Radar and Communications Automatic Target Recognition
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ISBN 10: 163081637X
ISBN 13: 9781630816377
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Modern Machine Learning Algorithms for Radar and Communicati
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Condition: New. Klappentext This exciting resource identifies technical challenges, benefits, and directions of Deep Learning (DL) based object classification using radar data (i.e., Synthetic Aperture Radar / SAR and High range resolution Radar / HRR d. Seller Inventory # 367982555
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Modern Machine Learning Algorithms for Radar and Communications
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Deep Learning for Radar and Communications Automatic Target Recognition
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