This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.
Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings.
Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.
"Sinopsis" puede pertenecer a otra edición de este libro.
This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.
Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings.
Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Paperback. Condición: new. Paperback. This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783031124129
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhanceme. Nº de ref. del artículo: 668447239
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings. Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden. 860 pp. Englisch. Nº de ref. del artículo: 9783031124129
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Taschenbuch. Condición: Neu. Third International Conference on Image Processing and Capsule Networks | ICIPCN 2022 | Joy Iong-Zong Chen (u. a.) | Taschenbuch | xv | Englisch | 2022 | Springer International Publishing | EAN 9783031124129 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 122039747
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Taschenbuch. Condición: Neu. Neuware -This book provides a collection of the state-of-the-art research attempts to tackle the challenges in image and signal processing from various novel and potential research perspectives. The book investigates feature extraction techniques, image enhancement methods, reconstruction models, object detection methods, recommendation models, deep and temporal feature analysis, intelligent decision support systems, and autonomous image detection models. In addition to this, the book also looks into the potential opportunities to monitor and control the global pandemic situations.Image processing technology has progressed significantly in recent years, and it has been commercialized worldwide to provide superior performance with enhanced computer/machine vision, video processing, and pattern recognition capabilities. Meanwhile, machine learning systems like CNN and CapsNet get popular to provide better model hierarchical relationships and attempts to more closely mimic biological neural organization. As machine learning systems prosper, image processing and machine learning techniques will be tightly intertwined and continuously promote each other in real-world settings.Adopting this trend, however, the image processing researchers are faced with few image reconstruction, analysis, and segmentation challenges. On the application side, the orientation of the image features and noise removal has become a huge burden.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 860 pp. Englisch. Nº de ref. del artículo: 9783031124129
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