A Comparative Analysis of Deep Learning Techniques for Sub-Tropical Crop Types Recognition from Multitemporal Optical/SAR Image Sequences

Proceedings - 30th Conference on Graphics, Patterns and Images, SIBGRAPI 2017

Volumn , Issue , 2017, Pages 382-389

  Castro, Jose David Bermudez ^a   Feitoza, Raul Queiroz ^a,b   Rosa, Laura Cue La ^a   Diaz, Pedro Marco Achanccaray ^a   Sanches, Ieda Del Arco ^c  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b STATE UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^c INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS   (Brazil)

Author keywords

Autoencoders; Convolutional Neural Networks; Crop Recognition; Multitemporal Images

Indexed keywords

AGRICULTURE; CLASSIFICATION (OF INFORMATION); CONVOLUTION; CROPS; DEEP LEARNING; LEARNING SYSTEMS; NEURAL NETWORKS; REMOTE SENSING; SYNTHETIC APERTURE RADAR;

AGRICULTURAL PRACTICES; AUTOENCODERS; CONVOLUTIONAL NEURAL NETWORK; CROP RECOGNITION; CROP TYPE CLASSIFICATION; MULTI-TEMPORAL IMAGE; STATE-OF-THE-ART TECHNIQUES; TRADITIONAL APPROACHES;

IMAGE ANALYSIS;

EID: 85040603108     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIBGRAPI.2017.57     Document Type: Conference Paper

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