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.
Details
Title
Augmenting a convolutional neural network with local histograms : a case study in crop classification from high-resolution UAV imagery
Author(s)
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)
Date
2016-04
Published in
Proceedings of ESANN 2016, European Symposium on artifical neural networks, Computational Intelligence and Machine Learning, 27-29 April 2016, Bruges, Belgium
Volume
2016, Article no. ES2016-74, pp. 515-520
Publisher
Bruges, Belgium, 27-29 April 2016
Pagination
6 p.
Presented at
European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, 2016-04-27, 2016-04-29
Paper 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