Articoli correlati a Biologically Inspired Hexagonal Deep Learning for Hexagonal...

Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Processing - Brossura

 
9783961002139: Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Processing
  • ISBN 10 3961002134
  • ISBN 13 9783961002139
  • RilegaturaCopertina flessibile
  • LinguaInglese
  • Numero di pagine300
  • Contatto del produttorenon disponibile

EUR 11,00 per la spedizione da Germania a Italia

Destinazione, tempi e costi

Risultati della ricerca per Biologically Inspired Hexagonal Deep Learning for Hexagonal...

Immagini fornite dal venditore

Tobias Schlosser
ISBN 10: 3961002134 ISBN 13: 9783961002139
Nuovo Taschenbuch
Print on Demand

Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -While current approaches to digital image processing in the context of deep learning are motivated by biological processes in the human brain, they are, however, also limited due to the current state of the art of input and output devices. To generate images from real-world scenes, the underlying lattice formats are predominantly based on rectangular or square structures. Yet, the human visual perception system suggests an alternative approach that manifests itself in the sensory cells of the human eye in the form of hexagonal arrangements.This contribution is therefore concerned with the design, implementation, and evaluation of hexagonal solutions in the form of hexagonal deep neural networks (H-DNN). The realized hexagonal functionality had to be built from the ground up as hexagonal counterparts to otherwise conventional square image processing systems, for which hexagonal equivalents for artificial neural network operations, layers, and models had to be implemented.To enable their evaluation, a set of different application areas within astronomical, medical, and industrial image processing are provided that allow an assessment of H-DNNs in terms of their general performance. The presented results demonstrate the possible benefits of H-DNNs for image processing systems. It is shown that H-DNNs can result in increased classification capabilities given different basic geometric shapes and contours, which in turn partially translate into their real-world applications. 272 pp. Englisch. Codice articolo 9783961002139

Contatta il venditore

Compra nuovo

EUR 32,90
Convertire valuta
Spese di spedizione: EUR 11,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Tobias Schlosser
ISBN 10: 3961002134 ISBN 13: 9783961002139
Nuovo Taschenbuch
Print on Demand

Da: AHA-BUCH GmbH, Einbeck, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - While current approaches to digital image processing in the context of deep learning are motivated by biological processes in the human brain, they are, however, also limited due to the current state of the art of input and output devices. To generate images from real-world scenes, the underlying lattice formats are predominantly based on rectangular or square structures. Yet, the human visual perception system suggests an alternative approach that manifests itself in the sensory cells of the human eye in the form of hexagonal arrangements.This contribution is therefore concerned with the design, implementation, and evaluation of hexagonal solutions in the form of hexagonal deep neural networks (H-DNN). The realized hexagonal functionality had to be built from the ground up as hexagonal counterparts to otherwise conventional square image processing systems, for which hexagonal equivalents for artificial neural network operations, layers, and models had to be implemented.To enable their evaluation, a set of different application areas within astronomical, medical, and industrial image processing are provided that allow an assessment of H-DNNs in terms of their general performance. The presented results demonstrate the possible benefits of H-DNNs for image processing systems. It is shown that H-DNNs can result in increased classification capabilities given different basic geometric shapes and contours, which in turn partially translate into their real-world applications. Codice articolo 9783961002139

Contatta il venditore

Compra nuovo

EUR 32,90
Convertire valuta
Spese di spedizione: EUR 14,99
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 2 disponibili

Aggiungi al carrello

Immagini fornite dal venditore

Tobias Schlosser
ISBN 10: 3961002134 ISBN 13: 9783961002139
Nuovo Taschenbuch

Da: preigu, Osnabrück, Germania

Valutazione del venditore 5 su 5 stelle 5 stelle, Maggiori informazioni sulle valutazioni dei venditori

Taschenbuch. Condizione: Neu. Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Processing | Tobias Schlosser | Taschenbuch | Englisch | Universitätsverlag Chemnitz | EAN 9783961002139 | Verantwortliche Person für die EU: preigu, Ansas Meyer, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 129323437

Contatta il venditore

Compra nuovo

EUR 32,90
Convertire valuta
Spese di spedizione: EUR 45,00
Da: Germania a: Italia
Destinazione, tempi e costi

Quantità: 5 disponibili

Aggiungi al carrello