| A context-sensitive technique for unsupervised change detection based on Hopfield-type neural networks S Ghosh, L Bruzzone, S Patra, F Bovolo, A Ghosh IEEE Transactions on Geoscience and Remote Sensing 45 (3), 778-789, 2007 | 180 | 2007 |
| Hyperspectral Band Selection Based on Rough Set S Patra, P Modi, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing 53 (10), 5495-5503, 2015 | 103 | 2015 |
| A fast cluster-assumption based active-learning technique for classification of remote sensing images S Patra, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing 49 (5), 1617-1626, 2010 | 102 | 2010 |
| Histogram thresholding for unsupervised change detection of remote sensing images S Patra, S Ghosh, A Ghosh International journal of remote sensing 32 (21), 6071-6089, 2011 | 99 | 2011 |
| A novel context sensitive multilevel thresholding for image segmentation S Patra, R Gautam, A Singla Applied soft computing 23, 122-127, 2014 | 97 | 2014 |
| A Novel SOM-SVM-Based Active Learning Technique for Remote Sensing Image Classification S Patra, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing 52 (11), 6899-6910, 2014 | 78 | 2014 |
| A cluster-assumption based batch mode active learning technique S Patra, L Bruzzone Pattern Recognition Letters 33 (9), 1042-1048, 2012 | 68 | 2012 |
| A batch-mode active learning technique based on multiple uncertainty for SVM classifier S Patra, L Bruzzone IEEE Geoscience and Remote Sensing Letters 9 (3), 497-501, 2011 | 62 | 2011 |
| A spectral-spatial multicriteria active learning technique for hyperspectral image classification S Patra, K Bhardwaj, L Bruzzone IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 51 | 2017 |
| An unsupervised context-sensitive change detection technique based on modified self-organizing feature map neural network S Ghosh, S Patra, A Ghosh International Journal of Approximate Reasoning 50, 37-50, 2009 | 51 | 2009 |
| A fast automatic optimal threshold selection technique for image segmentation A Singla, S Patra Signal, Image and Video Processing 11 (2), 243-250, 2017 | 50 | 2017 |
| Variable precision rough set based unsupervised band selection technique for hyperspectral image classification B Barman, S Patra Knowledge-Based Systems 193, 105414, 2020 | 44 | 2020 |
| An unsupervised technique for optimal feature selection in attribute profiles for spectral-spatial classification of hyperspectral images K Bhardwaj, S Patra ISPRS journal of photogrammetry and remote sensing 138, 139-150, 2018 | 42 | 2018 |
| A novel classification technique based on progressive transductive SVM learning A Singla, S Patra, L Bruzzone Pattern Recognition Letters 42, 101-106, 2014 | 36 | 2014 |
| Change detection of remote sensing images with semi-supervised multilayer perceptron S Patra, S Ghosh, A Ghosh Fundamenta Informaticae 84 (3-4), 429-442, 2008 | 34 | 2008 |
| Unsupervised change detection in remote-sensing images using modified self-organizing feature map neural network S Patra, S Ghosh, A Ghosh 2007 International Conference on Computing: Theory and Applications (ICCTA …, 2007 | 23 | 2007 |
| A novel dependency definition exploiting boundary samples in rough set theory for hyperspectral band selection S Patra, B Barman Applied Soft Computing 99, 106944, 2021 | 15 | 2021 |
| Threshold-free Attribute Profile for Classification of Hyperspectral Images K Bhardwaj, S Patra, L Bruzzone IEEE Transactions on Geoscience and Remote Sensing 57 (10), 7731-7742, 2019 | 15 | 2019 |
| Semi-supervised learning with multilayer perceptron for detecting changes of remote sensing images S Patra, S Ghosh, A Ghosh Pattern Recognition and Machine Intelligence: Second International …, 2007 | 15 | 2007 |
| Empirical study of neighbourhood rough sets based band selection techniques for classification of hyperspectral images B Barman, S Patra IET Image Processing 13 (8), 1266-1279, 2019 | 14 | 2019 |
Lorenzo BruzzoneProfessor of Telecommunications, University of TrentoVerified email at ing.unitn.it
