Articoli correlati a A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES:...
Sinossi
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
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES:...
Immagini fornite dal venditore
A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES
Editore:
LAP LAMBERT Academic Publishing Okt 2022, 2022
ISBN 10: 6204953052
ISBN 13: 9786204953052
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 9786204953052
Compra nuovo
EUR 43,90
Spedizione EUR 23,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Immagini fornite dal venditore
A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204953052
ISBN 13: 9786204953052
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: 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. Codice articolo 753796224
Compra nuovo
EUR 35,62
Spedizione EUR 48,99
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES : Neural Network
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204953052
ISBN 13: 9786204953052
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 9786204953052
Compra nuovo
EUR 49,63
Spedizione EUR 35,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES
Editore:
LAP LAMBERT Academic Publishing Okt 2022, 2022
ISBN 10: 6204953052
ISBN 13: 9786204953052
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 9786204953052
Compra nuovo
EUR 43,90
Spedizione EUR 60,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
A NEURAL NETWORK APPROACH FOR COUNTING NUMBER OF IMAGES | Neural Network
Editore:
LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6204953052
ISBN 13: 9786204953052
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: 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. Codice articolo 125799790
Compra nuovo
EUR 39,45
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili