| Deep feature extraction and classification of hyperspectral images based on convolutional neural networks Y Chen, H Jiang, C Li, X Jia, P Ghamisi IEEE transactions on geoscience and remote sensing 54 (10), 6232-6251, 2016 | 2666 | 2016 |
| Spectral–spatial classification of hyperspectral data based on deep belief network Y Chen, X Zhao, X Jia IEEE journal of selected topics in applied earth observations and remote …, 2015 | 1263 | 2015 |
| Segmented principal components transformation for efficient hyperspectral remote-sensing image display and classification X Jia, JA Richards IEEE transactions on Geoscience and Remote Sensing 37 (1), 538-542, 1999 | 557 | 1999 |
| Feature mining for hyperspectral image classification X Jia, BC Kuo, MM Crawford Proceedings of the IEEE 101 (3), 676-697, 2013 | 437 | 2013 |
| Hyperspectral images classification with Gabor filtering and convolutional neural network Y Chen, L Zhu, P Ghamisi, X Jia, G Li, L Tang IEEE Geoscience and Remote Sensing Letters 14 (12), 2355-2359, 2017 | 248 | 2017 |
| Nonlinear multiple kernel learning with multiple-structure-element extended morphological profiles for hyperspectral image classification Y Gu, T Liu, X Jia, JA Benediktsson, J Chanussot IEEE Transactions on Geoscience and Remote Sensing 54 (6), 3235-3247, 2016 | 237 | 2016 |
| Multiple kernel learning for hyperspectral image classification: A review Y Gu, J Chanussot, X Jia, JA Benediktsson IEEE Transactions on Geoscience and Remote Sensing 55 (11), 6547-6565, 2017 | 228 | 2017 |
| Adaptive Markov random field approach for classification of hyperspectral imagery B Zhang, S Li, X Jia, L Gao, M Peng IEEE Geoscience and Remote Sensing Letters 8 (5), 973-977, 2011 | 219 | 2011 |
| Deep fusion of remote sensing data for accurate classification Y Chen, C Li, P Ghamisi, X Jia, Y Gu IEEE Geoscience and Remote Sensing Letters 14 (8), 1253-1257, 2017 | 200 | 2017 |
| Efficient maximum likelihood classification for imaging spectrometer data sets X Jia, JA Richards IEEE Transactions on Geoscience and Remote Sensing 32 (2), 274-281, 1994 | 188 | 1994 |
| Hyperspectral image classification using convolutional neural networks and multiple feature learning Q Gao, S Lim, X Jia Remote Sensing 10 (2), 299, 2018 | 183 | 2018 |
| Foreword to the special issue on spectral unmixing of remotely sensed data A Plaza, Q Du, JM Bioucas-Dias, X Jia, FA Kruse IEEE transactions on geoscience and remote sensing 49 (11), 4103-4110, 2011 | 179 | 2011 |
| SpectralGPT: Spectral foundation model D Hong, B Zhang, X Li, Y Li, C Li, J Yao, N Yokoya, H Li, X Jia, A Plaza, ... arXiv preprint arXiv:2311.07113, 2023 | 157 | 2023 |
| Deep learning ensemble for hyperspectral image classification Y Chen, Y Wang, Y Gu, X He, P Ghamisi, X Jia IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 143 | 2019 |
| Integration of soft and hard classifications using extended support vector machines L Wang, X Jia IEEE Geoscience and Remote Sensing Letters 6 (3), 543-547, 2009 | 124 | 2009 |
| A novel semisupervised active-learning algorithm for hyperspectral image classification Z Wang, B Du, L Zhang, L Zhang, X Jia IEEE Transactions on Geoscience and Remote Sensing 55 (6), 3071-3083, 2017 | 123 | 2017 |
| A comparison of information value and logistic regression models in landslide susceptibility mapping by using GIS T Chen, R Niu, X Jia Environmental Earth Sciences 75, 1-16, 2016 | 113 | 2016 |
| A novel MKL model of integrating LiDAR data and MSI for urban area classification Y Gu, Q Wang, X Jia, JA Benediktsson IEEE transactions on geoscience and remote sensing 53 (10), 5312-5326, 2015 | 112 | 2015 |
| Effective sequential classifier training for SVM-based multitemporal remote sensing image classification Y Guo, X Jia, D Paull IEEE Transactions on Image Processing 27 (6), 3036-3048, 2018 | 111 | 2018 |
| Cloud removal based on sparse representation via multitemporal dictionary learning M Xu, X Jia, M Pickering, AJ Plaza IEEE Transactions on Geoscience and Remote Sensing 54 (5), 2998-3006, 2016 | 108 | 2016 |
Mark PickeringUNSW Canberra在 adfa.edu.au 的电子邮件经过验证
