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.
Einzelheiten
Titel
Augmenting a convolutional neural network with local histograms : a case study in crop classification from high-resolution UAV imagery
Autor(en)/ in(nen)
Rebetez, Julien (School of Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts Western Switzerland) Satizábal, Héctor F. (School of Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts 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 Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts Western Switzerland) Perez-Uribe, Andres (School of Engineering and Management Vaud, HES-SO, University of Applied Sciences and Arts Western Switzerland) Burgos, Stéphane (Bern University of Applied Sciences, School of Agricultural, Forest and Food Sciences HAFL, Zollikofen, Switzerland)
Datum
2016-04
Veröffentlich in
Proceedings of ESANN 2016, European Symposium on artifical neural networks, Computational Intelligence and Machine Learning, 27-29 April 2016, Bruges, Belgium
Band
2016, Article no. ES2016-74, pp. 515-520
Verlag
Bruges, Belgium, 27-29 April 2016
Umfang
6 p.
Vorgestellt auf
European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, 2016-04-27, 2016-04-29
Papiertyp
full paper
Domaine
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