Multi swarm optimization methodology von chandra prasad (6 Ergebnisse)
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Paperback. Zustand: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.
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Taschenbuch. Zustand: Neu. Multi Swarm Optimization Methodology for Classification of Images | Classification of Images | G. Shyama Chandra Prasad | Taschenbuch | 52 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200277534 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078… Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine recognition by human beings from still and video images has become a very important and vigorous area of research in the communities of image processing, pattern recognition, neural networks and computer vision. Image recognit…ion is one of the most extraordinary abilities of human vision. The core and central part of the image research is classification and extracting. Although image recognition by human beings and computer machines are developed, it is still challenging to design an automatic system for the given task. The reason is that illumination, complex background, visual angle and variation expression for images are highly variable in the real world. Several techniques have been proposed for image detection including graph matching, neural networks and geometric features. Even though researchers of Psychology, Neural Sciences, Engineering, Image Processing and Computer Vision have investigated a number of issues related to image recognition by human beings and machines, still there is need to design an automatic system for this task, especially when real-time identification is required. 52 pp. Englisch.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chandra Prasad G. ShyamaDr G. Shyama Chandra Prasad - B.Tech. (CSE), M.Tech.(CS), Ph.D. Associate Professor, is working as Associate Professor in Matrusri Engineering College, Hyderabad, India. He served…and held several Academic and.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Machine recognition by human beings from still and video images has become a very important and vigorous area of research in the communities of image processing, pattern recognition, neural networks and computer vision. Image recognition…is one of the most extraordinary abilities of human vision. The core and central part of the image research is classification and extracting. Although image recognition by human beings and computer machines are developed, it is still challenging to design an automatic system for the given task. The reason is that illumination, complex background, visual angle and variation expression for images are highly variable in the real world. Several techniques have been proposed for image detection including graph matching, neural networks and geometric features. Even though researchers of Psychology, Neural Sciences, Engineering, Image Processing and Computer Vision have investigated a number of issues related to image recognition by human beings and machines, still there is need to design an automatic system for this task, especially when real-time identification is required.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Machine recognition by human beings from still and video images has become a very important and vigorous area of research in the communities of image processing, pattern recognition, neural networks and computer vision. Image recognition i…s one of the most extraordinary abilities of human vision. The core and central part of the image research is classification and extracting. Although image recognition by human beings and computer machines are developed, it is still challenging to design an automatic system for the given task. The reason is that illumination, complex background, visual angle and variation expression for images are highly variable in the real world. Several techniques have been proposed for image detection including graph matching, neural networks and geometric features. Even though researchers of Psychology, Neural Sciences, Engineering, Image Processing and Computer Vision have investigated a number of issues related to image recognition by human beings and machines, still there is need to design an automatic system for this task, especially when real-time identification is required.
