Ortega, M., Castro, J. B., Soto, P., & Feitosa, R. Q. (2018, November). Unsupervised Representation Learning for Classification of Remote Sensing images based on Generative Adversarial Networks. GRSS-YP & ISPRS Student Consortium SS 2018, Campo Grande (pp. 46).
2018
Proof of concept of a novel cloud computing approach for object-based remote sensing data analysis and classification
Antunes, R. R., Blaschke, T., Tiede, D., Bias, E. S., Costa, G. A. O. P. and Happ, P. N.: Proof of concept of a novel cloud computing approach for object-based remote sensing data analysis and classification GIScience & Remote Sensing, 2018
An Hybrid Recurrent Convolutional Neural Network for Crop Type Recognition Based on Multitemporal Sar Image Sequences
Castro, J. B., Feitosa, R. Q., & Happ, P. N. (2018, July). An Hybrid Recurrent Convolutional Neural Network for Crop Type Recognition Based on Multitemporal Sar Image Sequences. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 3824-3827). IEEE.
Dense Fully Convolutional Networks for Crop Recognition from Multitemporal SAR Image Sequences
La Rosa, L. E. C., Happ, P. N., & Feitosa, R. Q. (2018, July). Dense Fully Convolutional Networks for Crop Recognition from Multitemporal SAR Image Sequences. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 7460-7463). IEEE.
SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKS
Bermudez, J. D., Happ, P. N., Oliveira, D. A. B., and Feitosa, R. Q.: SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKS., ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1, 5-11, https://doi.org/10.5194/isprs-annals-IV-1-5-2018, 2018.
LEM Benchmark database for tropical agricultural remote sensing application
Sanches, I. D., Feitosa, R. Q., Achanccaray, P., Montibeller, B., Luiz, A. J. B., Soares, M. D., Prudente, V. H. R., Vieira, D. C., and Maurano, L. E. P.: LEM Benchmark database for tropical agricultural remote sensing application., Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-1, 387-392, https://doi.org/10.5194/isprs-archives-XLII-1-387-2018, 2018.
Campo Verde Database: Seeking to improve agricultural remote sensing of tropical areas
Sanches, I. D.; Feitosa, R. Q.; Achanccaray, P.; Soares, M. D.; Luiz, A.; Schultz, B.; Maurano, L. Campo Verde Database: Seeking to improve agricultural remote sensing of tropical areas. IEEE Geoscience and Remote Sensing Letters, 15(3):369-373, 2018.