Machine learning based hyperspectral image analysis: a survey UB Gewali, ST Monteiro, E Saber arXiv preprint arXiv:1802.08701, 2018 | 170 | 2018 |
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 | 157 | 2012 |
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 | 127 | 2007 |
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 | 111 | 2017 |
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 | 106 | 2013 |
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 | 73 | 2010 |
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 | 60 | 2014 |
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 | 51 | 2016 |
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 | 48 | 2018 |
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 | 46 | 2019 |
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 | 37 | 2014 |
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 | 37 | 2010 |
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 | 36 | 2015 |
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 | 28 | 2019 |
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 | 26 | 2011 |
A particle swarm optimization-based approach for hyperspectral band selection ST Monteiro, Y Kosugi 2007 IEEE Congress on Evolutionary Computation, 3335-3340, 2007 | 26 | 2007 |
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 | 25 | 2004 |
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 | 22 | 2012 |
Spectral super-resolution with optimized bands UB Gewali, ST Monteiro, E Saber Remote Sensing 11 (14), 1648, 2019 | 21 | 2019 |
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 | 21 | 2004 |