While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.
The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI.
This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence.
"synopsis" may belong to another edition of this title.
Dr Chen received his PhD from Purdue University in 1965, MS degree from Univ. of Tennessee Knoxville in 1962 and his BS from National Taiwan University in 1959, all in electrical engineering. His research Is in pattern recognition, computer vision, signal and image processing with applications to remote sensing, underwater acoustics, geophysics, etc. He retired in 2010 as chancellor professor from University of Massachusetts Dartmouth after serving on the faculty for 42 years. He was editor of the series Handbook of Pattern Recognition and Computer Vision vol. 1–6 (1993 to 2020) for World Scientific Publishing. He is the book series editor in computer vision for World Scientific Publishing, and book series editor in Signal and Image Processing for Remote Sensing for CRC Press. He has authored and edited 36 books in his research areas.
"About this title" may belong to another edition of this title.
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Hardcover. Condition: new. Hardcover. While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI. This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789819807147
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Hardback. Condition: New. While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI. This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence. Seller Inventory # LU-9789819807147
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Hardback. Condition: New. While traditional approaches in pattern recognition and computer vision have continued to evolve, along with the advances of artificial intelligence (AI), this unique compendium presents recent research activities in deep learning, graph-based and semantic-based approaches and applications.The book covers the most recent advances as well as traditional topics in pattern recognition and computer vision in this new AI area in the first part. The second part presents emerging applications of deep learning and AI. This useful reference text benefits academics, professionals, researchers and graduate students in pattern recognition, computer vision, image segmentation and artificial intelligence. Seller Inventory # LU-9789819807147
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