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2019

MAPPING GLACIER CHANGES USING CLUSTERING TECHNIQUES ON CLOUD COMPUTING INFRASTRUCTURE

Ayma, V., C. Beltrán, P. N. Happ, G. A. O. P. Costa, and R. Q. Feitosa. “MAPPING GLACIER CHANGES USING CLUSTERING TECHNIQUES ON CLOUD COMPUTING INFRASTRUCTURE.” International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences (2019).

Combining deep learning and prior knowledge for crop mapping in tropical regions from multitemporal SAR image sequences

Cué La Rosa, Laura Elena, Raul Queiroz Feitosa, Patrick Nigri Happ, Ieda Del’Arco Sanches, and Gilson Alexandre Ostwald Pedro da Costa. “Combining deep learning and prior knowledge for crop mapping in tropical regions from multitemporal SAR image sequences.” Remote Sensing 11, no. 17 (2019): 2029.

Assessment of CNN-based methods for individual tree detection on images captured by RGB cameras attached to UAVs

Santos, Anderson Aparecido dos, Jose Marcato Junior, Márcio Santos Araújo, David Robledo Di Martini, Everton Castelão Tetila, Henrique Lopes Siqueira, Camila Aoki et al. “Assessment of CNN-based methods for individual tree detection on images captured by RGB cameras attached to UAVs.” Sensors 19, no. 16 (2019): 3595.

A COMPARISON BETWEEN THE HADOOP AND SPARK DISTRIBUTED FRAMEWORKS IN THE CONTEXT OF REGION-GROWING SEGMENTATION OF REMOTE SENSING IMAGES

Andrade, R. B., J. M. F. Santos, G. A. O. P. Costa, G. L. A. Mota, P. N. Happ, and R. Q. Feitosa. “A COMPARISON BETWEEN THE HADOOP AND SPARK DISTRIBUTED FRAMEWORKS IN THE CONTEXT OF REGION-GROWING SEGMENTATION OF REMOTE SENSING IMAGES.” ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences 4 (2019).

IEEE GRSS Brazil Chapter: Status and Activities in 2019

Liesenberg, Veraldo, Jose Marcato, Raul Queiroz Feitosa, Alessandra Rodrigues Gomes, Jefersson Alex Dos Santos, Rafael Lemos Paes, Edson A. Mitishita, Antonio MG Tommaselli, Fatima N. Sombra de Sombra, and Alejandro C. Frery. “IEEE GRSS Brazil Chapter: Status and Activities in 2019 [Chapters].” IEEE Geoscience and Remote Sensing Magazine 8, no. 4 (2020): 144-151.

A Many-To-Many Fully Convolutional Recurrent Network For Multitemporal Crop Recognition

Chamorro, J. A., Castro, J. B., Happ, P. N. & Feitosa, R. Q. (2019, September). A Many-To-Many Fully Convolutional Recurrent Network For Multitemporal Crop Recognition. PIA19+MRSS19 – Photogrammetric Image Analysis & Munich Remote Sensing Symposium 2019, Munich, Germany.

Evaluation of Deep Learning techniques for deforestation detection in the Amazon Forest

Ortega, M. X., Bermudez J.D, Happ, P. N., Gomes, A., & Feitosa, R. Q. (2019, September). Evaluation of Deep Learning techniques for deforestation detection in the Amazon Forest. PIA19+MRSS19 – Photogrammetric Image Analysis & Munich Remote Sensing Symposium 2019, Munich, Germany.

A COMPARATIVE ANALYSIS OF UNSUPERVISED AND SEMI-SUPERVISED REPRESENTATION LEARNING FOR REMOTE SENSING IMAGE CATEGORIZATION

Soto, P. J., Bermudez, J. D., Happ, P. N., and Feitosa, R. Q.: A COMPARATIVE ANALYSIS OF UNSUPERVISED AND SEMI-SUPERVISED REPRESENTATION LEARNING FOR REMOTE SENSING IMAGE CATEGORIZATION, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W7, 167–173, 2019.

Synthesis of Multispectral Optical Images From SAR/Optical Multitemporal Data Using Conditional Generative Adversarial Networks

BERMUDEZ, JOSE D.; HAPP, PATRICK N.; FEITOSA, RAUL Q.; OLIVEIRA, DARIO A. B. Synthesis of Multispectral Optical Images From SAR/Optical Multitemporal Data Using Conditional Generative Adversarial Networks. IEEE Geoscience and Remote Sensing Letters

MAPPING EUCALYPTUS PLANTATIONS AND NATURAL FOREST AREAS IN LANDSAT-TM IMAGES USING DEEP LEARNING

Ferreira, P. M., La Rosa, L. E. C., Happ, P. N., Theobald, R. B. & Feitosa, R. Q. (2019, April). MAPPING EUCALYPTUS PLANTATIONS AND NATURAL FOREST AREAS IN LANDSAT-TM IMAGES USING DEEP LEARNING. XIX Simpósio Brasileiro de Sensoriamento Remoto 2019, Santos, SP.

A Comparison Of Fully Convolutional And Recurrent Networks For Multi-Temporal Crop Recognition Using SAR Images

Chamorro, J. A., Happ, P. N., Castro, J. B., La Rosa, L. E. C., & Feitosa, R. Q. (2019, April). A Comparison Of Fully Convolutional And Recurrent Networks For Multi-Temporal Crop Recognition Using SAR Images. XIX Brazilian Symposium on Remote Sensing 2019, Santos, SP.

Assessment of an Early Fusion CNN Approach applied to the deforestation detection in the Brazilian Amazon

Ortega, M. X., Happ, P. N., & Feitosa, R. Q. (2019, April). Assessment of an Early Fusion CNN Approach applied to the deforestation detection in the Brazilian Amazon. XIX Simpósio Brasileiro de Sensoriamento Remoto 2019, Santos, SP.

© 2019 Computer Vision Lab