Improvement in Land Cover and Crop Classification based on Temporal
Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural
Network (R-CNN)

v1v2 (latest)

Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)

27 April 2020

Vittorio Mazzia

Marcello Chiaberge

ArXiv (abs)PDF HTML

Papers citing "Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)"

7 / 7 papers shown

Title
A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture Brandon Victor Zhen He Aiden Nibali 102 9 0 03 Oct 2022
Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks Nicolas Audebert Bertrand Le Saux Sébastien Lefèvre 90 516 0 23 Nov 2017
Cyclical Learning Rates for Training Neural Networks L. Smith ODL 212 2,533 0 03 Jun 2015
Gated Feedback Recurrent Neural Networks Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 72 830 0 09 Feb 2015
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling Junyoung Chung Çağlar Gülçehre Kyunghyun Cho Yoshua Bengio 593 12,734 0 11 Dec 2014
Sequence to Sequence Learning with Neural Networks Ilya Sutskever Oriol Vinyals Quoc V. Le AIMat 437 20,584 0 10 Sep 2014
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,893 0 12 Nov 2013