Augmenting a convolutional neural network with local histograms : a case study in crop classification from high-resolution UAV imagery

Rebetez, Julien (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Satizábal, Héctor F. (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Mota, Matteo (School of Viticulture and Enology, HES-SO // University of Applied Sciences Western Switzerland) ; Noll, Dorothea (School of Viticulture and Enology, HES-SO // University of Applied Sciences Western Switzerland) ; Büchi, Lucie (Agroscope, Institut for Plant Production Sciences, Nyon, Switzerland) ; Wendling, Marina (Agroscope, Institut for Plant Production Sciences, Nyon, Switzerland) ; Cannelle, Bertrand (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Perez-Uribe, Andres (School of Management and Engineering Vaud, HES-SO // University of Applied Sciences Western Switzerland) ; Burgos, Stéphane (Bern University of Applied Sciences, School of Agricultural, Forest and Food Sciences HAFL, Zollikofen, Switzerland)

The advent of affordable drones capable of taking high resolution images of agricultural fields creates new challenges and opportunities in aerial scene understanding. This paper tackles the problem of recognizing crop types from aerial imagery and proposes a new hybrid neural network architecture which combines histograms and convolutional units. We evaluate the performance of the proposed model on a 23-class classification task and compare it to other models. The result is an improvement of the classification performance.


Type de conférence:
full paper
Faculté:
Ingénierie et Architecture
Ecole:
HEIG-VD
Changins
Institut:
IICT - Institut des Technologies de l'Information et de la Communication
insit - Institut d’ingénierie du territoire
Adresse bibliogr.:
Bruges, Belgium, 27-29 April 2016
Date:
2016-04
Bruges, Belgium
27-29 April 2016
Pagination:
6 p.
Veröffentlicht in:
Proceedings of ESANN 2016, European Symposium on artifical neural networks, Computational Intelligence and Machine Learning, 27-29 April 2016, Bruges, Belgium
Numérotation (vol. no.):
2016, Article no. ES2016-74, pp. 515-520
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 Datensatz erzeugt am 2020-02-25, letzte Änderung am 2020-10-27

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