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.


Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEIG-VD
Changins
Institute:
IICT - Institut des Technologies de l'Information et de la Communication
insit - Institut d’ingénierie du territoire
Publisher:
Bruges, Belgium, 27-29 April 2016
Date:
2016-04
Bruges, Belgium
27-29 April 2016
Pagination:
6 p.
Published in:
Proceedings of ESANN 2016, European Symposium on artifical neural networks, Computational Intelligence and Machine Learning, 27-29 April 2016, Bruges, Belgium
Numeration (vol. no.):
2016, Article no. ES2016-74, pp. 515-520
Appears in Collection:



 Record created 2020-02-25, last modified 2020-02-25

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