Crowd counting is a dominant topic of research in the field of computer surveillance, but if the crowd distribution is unequal the perfection of crowd counting on the basis of the MCNN has yet to be improved to adapt to uneven crowd distributions MCNN has been used to perform aggressive results. The global density feature for crowds in a project is taken into account, and globalised density aspects are drawn and added to the MCNN by the cascaded learning method, because in the course of the down-sampling process certain comprehensive features will be disregarded by the MCNN, and this will affect the precision of the density map. The experimental results for ucfcc50 and the shanghaitech data set indicate that the method proposed is more accurate and more stable
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Crowd counting is a dominant topic of research in the field of computer surveillance, but if the crowd distribution is unequal the perfection of crowd counting on the basis of the MCNN has yet to be improved to adapt to uneven crowd distributions MCNN has been used to perform aggressive results. The global density feature for crowds in a project is taken into account, and globalised density aspects are drawn and added to the MCNN by the cascaded learning method, because in the course of the down-sampling process certain comprehensive features will be disregarded by the MCNN, and this will affect the precision of the density map. The experimental results for ucfcc50 and the shanghaitech data set indicate that the method proposed is more accurate and more stable 68 pp. Englisch. N° de réf. du vendeur 9786204953052
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: M Purushotham ReddyI am a professor in Information Technology, Institute of Aeronautical Engineering, Hyderabad and author for different books. I published 30+ articles in various journals.Crowd counting is a dominant topic of re. N° de réf. du vendeur 753796224
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Crowd counting is a dominant topic of research in the field of computer surveillance, but if the crowd distribution is unequal the perfection of crowd counting on the basis of the MCNN has yet to be improved to adapt to uneven crowd distributions MCNN has been used to perform aggressive results. The global density feature for crowds in a project is taken into account, and globalised density aspects are drawn and added to the MCNN by the cascaded learning method, because in the course of the down-sampling process certain comprehensive features will be disregarded by the MCNN, and this will affect the precision of the density map. The experimental results for ucfcc50 and the shanghaitech data set indicate that the method proposed is more accurate and more stable. N° de réf. du vendeur 9786204953052
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Crowd counting is a dominant topic of research in the field of computer surveillance, but if the crowd distribution is unequal the perfection of crowd counting on the basis of the MCNN has yet to be improved to adapt to uneven crowd distributions MCNN has been used to perform aggressive results. The global density feature for crowds in a project is taken into account, and globalised density aspects are drawn and added to the MCNN by the cascaded learning method, because in the course of the down-sampling process certain comprehensive features will be disregarded by the MCNN, and this will affect the precision of the density map. The experimental results for ucfcc50 and the shanghaitech data set indicate that the method proposed is more accurate and more stableVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. N° de réf. du vendeur 9786204953052
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Taschenbuch. Etat : Neu. A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES | Neural Network | Purushotham Reddy M | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204953052 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 125799790
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