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Keiller Nogueira
Tytuł
Cytowane przez
Cytowane przez
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Towards better exploiting convolutional neural networks for remote sensing scene classification
K Nogueira, OAB Penatti, JA Dos Santos
Pattern Recognition 61, 539-556, 2017
8482017
Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?
OAB Penatti, K Nogueira, JA Dos Santos
Proceedings of the IEEE conference on computer vision and pattern …, 2015
7482015
Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks
K Nogueira, M Dalla Mura, J Chanussot, WR Schwartz, JA Dos Santos
IEEE Transactions on Geoscience and Remote Sensing, 2019
892019
Improving spatial feature representation from aerial scenes by using convolutional networks
K Nogueira, WO Miranda, JA Dos Santos
2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, 289-296, 2015
602015
Exploiting ConvNet diversity for flooding identification
K Nogueira, SG Fadel, ÍC Dourado, RO Werneck, JAV Muñoz, ...
IEEE Geoscience and Remote Sensing Letters 15 (9), 1446-1450, 2018
522018
Learning to semantically segment high-resolution remote sensing images
K Nogueira, M Dalla Mura, J Chanussot, WR Schwartz, JA dos Santos
2016 23rd International Conference on Pattern Recognition (ICPR), 3566-3571, 2016
312016
An introduction to deep morphological networks
K Nogueira, J Chanussot, MD Mura, JA Santos
IEEE Access 9, 114308-114324, 2021
262021
Learning deep features on multiple scales for coffee crop recognition
R Baeta, K Nogueira, D Menotti, JA dos Santos
2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI …, 2017
202017
Towards vegetation species discrimination by using data-driven descriptors
K Nogueira, JA Dos Santos, T Fornazari, TSF Silva, LP Morellato, ...
2016 9th IAPR Workshop on Pattern Recogniton in Remote Sensing (PRRS), 1-6, 2016
202016
Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery
LP Osco, K Nogueira, AP Marques Ramos, MM Faita Pinheiro, ...
Precision Agriculture 22 (4), 1171-1188, 2021
182021
Data-Driven Flood Detection using Neural Networks
K Nogueira, SG Fadel, ÍC Dourado, RO Werneck, JAV Muñoz, ...
MediaEval, 2017
182017
Semantic segmentation of tree-canopy in urban environment with pixel-wise deep learning
JAC Martins, K Nogueira, LP Osco, FDG Gomes, DEG Furuya, ...
Remote Sensing 13 (16), 3054, 2021
172021
Benchmarking anchor-based and anchor-free state-of-the-art deep learning methods for individual tree detection in rgb high-resolution images
P Zamboni, JM Junior, JA Silva, GT Miyoshi, ET Matsubara, K Nogueira, ...
Remote Sensing 13 (13), 2482, 2021
162021
Coffee crop recognition using multi-scale convolutional neural networks
K Nogueira, WR Schwartz, JA dos Santos
Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2015
152015
Semantic segmentation of vegetation images acquired by unmanned aerial vehicles using an ensemble of ConvNets
K Nogueira, JA Dos Santos, L Cancian, BD Borges, TSF Silva, ...
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2017
132017
Towards open-set semantic segmentation of aerial images
CCV da Silva, K Nogueira, HN Oliveira, JA dos Santos
2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS), 16-21, 2020
112020
Pointwise and pairwise clothing annotation: combining features from social media
K Nogueira, AA Veloso, JA Dos Santos
Multimedia Tools and Applications 75, 4083-4113, 2016
112016
Fully convolutional open set segmentation
H Oliveira, C Silva, GLS Machado, K Nogueira, JA Dos Santos
Machine Learning, 1-52, 2021
102021
Spatio-temporal vegetation pixel classification by using convolutional networks
K Nogueira, JA dos Santos, N Menini, TSF Silva, LPC Morellato, ...
IEEE Geoscience and Remote Sensing Letters 16 (10), 1665-1669, 2019
102019
Airound and cv-brct: Novel multiview datasets for scene classification
G Machado, E Ferreira, K Nogueira, H Oliveira, M Brito, PHT Gama, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020
92020
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