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Sildomar T. Monteiro
Sildomar T. Monteiro
Aurora (Boeing) | MIT
Bestätigte E-Mail-Adresse bei mit.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Machine learning based hyperspectral image analysis: a survey
UB Gewali, ST Monteiro, E Saber
arXiv preprint arXiv:1802.08701, 2018
1832018
Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors
RJ Murphy, ST Monteiro, S Schneider
IEEE Transactions on Geoscience and Remote Sensing 50 (8), 3066-3080, 2012
1632012
Prediction of sweetness and amino acid content in soybean crops from hyperspectral imagery
ST Monteiro, Y Minekawa, Y Kosugi, T Akazawa, K Oda
ISPRS Journal of Photogrammetry and Remote Sensing 62 (1), 2-12, 2007
1292007
Dense semantic labeling of very-high-resolution aerial imagery and lidar with fully-convolutional neural networks and higher-order CRFs
Y Liu, S Piramanayagam, ST Monteiro, E Saber
Proceedings of the IEEE conference on computer vision and pattern …, 2017
1122017
Mapping the distribution of ferric iron minerals on a vertical mine face using derivative analysis of hyperspectral imagery (430–970 nm)
RJ Murphy, ST Monteiro
ISPRS Journal of Photogrammetry and Remote Sensing 75, 29-39, 2013
1112013
Rock recognition from MWD data: a comparative study of boosting, neural networks, and fuzzy logic
A Kadkhodaie-Ilkhchi, ST Monteiro, F Ramos, P Hatherly
IEEE Geoscience and Remote Sensing Letters 7 (4), 680-684, 2010
772010
Consistency of Measurements of Wavelength Position From Hyperspectral Imagery: Use of the Ferric Iron Crystal Field Absorption at 900 nm as an Indicator of Mineralogy
RJ Murphy, S Schneider, ST Monteiro
Geoscience and Remote Sensing, IEEE Transactions on 52 (5), 2843 - 2857, 2014
642014
Transfer learning for high resolution aerial image classification
Y Liang, ST Monteiro, ES Saber
2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 1-8, 2016
532016
Dual-channel densenet for hyperspectral image classification
G Yang, UB Gewali, E Ientilucci, M Gartley, ST Monteiro
IGARSS 2018-2018 IEEE international geoscience and remote sensing symposium …, 2018
502018
Semantic segmentation of multisensor remote sensing imagery with deep ConvNets and higher-order conditional random fields
Y Liu, S Piramanayagam, ST Monteiro, E Saber
Journal of Applied Remote Sensing 13 (1), 016501-016501, 2019
482019
Robust stock value prediction using support vector machines with particle swarm optimization
TM Sands, D Tayal, ME Morris, ST Monteiro
2015 IEEE Congress on Evolutionary Computation (CEC), 3327-3331, 2015
382015
Mapping layers of clay in a vertical geological surface using hyperspectral imagery: Variability in parameters of SWIR absorption features under different conditions of …
RJ Murphy, S Schneider, ST Monteiro
Remote Sensing 6 (9), 9104-9129, 2014
382014
3D geological modelling using laser and hyperspectral data
JI Nieto, ST Monteiro, D Viejo
2010 IEEE international geoscience and remote sensing symposium, 4568-4571, 2010
372010
Gaussian processes for vegetation parameter estimation from hyperspectral data with limited ground truth
UB Gewali, ST Monteiro, E Saber
Remote Sensing 11 (13), 1614, 2019
302019
A particle swarm optimization-based approach for hyperspectral band selection
ST Monteiro, Y Kosugi
2007 IEEE Congress on Evolutionary Computation, 3335-3340, 2007
272007
Embedded feature selection of hyperspectral bands with boosted decision trees
ST Monteiro, RJ Murphy
2011 IEEE International Geoscience and Remote Sensing Symposium, 2361-2364, 2011
262011
Towards applying hyperspectral imagery as an intraoperative visual aid tool
ST Monteiro, Y Kosugi, K Uto, E Watanabe
Proc. 4th Int. Conf. on Visualization, Imaging and Image Processing, 483-488, 2004
252004
Automatic rock recognition from drilling performance data
H Zhou, P Hatherly, ST Monteiro, F Ramos, F Oppolzer, E Nettleton, ...
2012 IEEE International Conference on Robotics and Automation, 3407-3412, 2012
232012
Spectral super-resolution with optimized bands
UB Gewali, ST Monteiro, E Saber
Remote Sensing 11 (14), 1648, 2019
222019
Desempenho de algoritmos de aprendizagem por reforço sob condições de ambiguidade sensorial em robótica móvel
ST Monteiro, CHC Ribeiro
Sba: Controle & Automação Sociedade Brasileira de Automatica 15, 320-338, 2004
222004
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