| Feature extraction for hyperspectral imagery: The evolution from shallow to deep: Overview and toolbox B Rasti, D Hong, R Hang, P Ghamisi, X Kang, J Chanussot, ... IEEE Geoscience and Remote Sensing Magazine 8 (4), 60-88, 2020 | 254 | 2020 |
| Cascaded recurrent neural networks for hyperspectral image classification R Hang, Q Liu, D Hong, P Ghamisi IEEE Transactions on Geoscience and Remote Sensing 57 (8), 5384-5394, 2019 | 237 | 2019 |
| Bidirectional-convolutional LSTM based spectral-spatial feature learning for hyperspectral image classification Q Liu, F Zhou, R Hang, X Yuan Remote Sensing 9 (12), 1330, 2017 | 188 | 2017 |
| Spatiotemporal satellite image fusion using deep convolutional neural networks H Song, Q Liu, G Wang, R Hang, B Huang IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 165 | 2018 |
| Learning Multiscale Deep Features for High-Resolution Satellite Image Scene Classification Q Liu, R Hang, H Song, Z Li IEEE Transactions on Geoscience and Remote Sensing 56 (1), 117-126, 2017 | 154* | 2017 |
| Hyperspectral image classification using spectral-spatial LSTMs F Zhou, R Hang, Q Liu, X Yuan Neurocomputing 328, 39-47, 2019 | 123 | 2019 |
| Classification of hyperspectral and LiDAR data using coupled CNNs R Hang, Z Li, P Ghamisi, D Hong, G Xia, Q Liu IEEE Transactions on Geoscience and Remote Sensing 58 (7), 4939-4950, 2020 | 84 | 2020 |
| Hyperspectral image classification with attention-aided CNNs R Hang, Z Li, Q Liu, P Ghamisi, SS Bhattacharyya IEEE Transactions on Geoscience and Remote Sensing 59 (3), 2281-2293, 2020 | 82 | 2020 |
| Stacked Sparse Autoencoder (SSAE) based framework for nuclei patch classification on breast cancer histopathology J Xu, L Xiang, R Hang, J Wu IEEE International Symposium on Biomedical Imaging (ISBI), 999-1002, 2014 | 82 | 2014 |
| Matrix-based discriminant subspace ensemble for hyperspectral image spatial–spectral feature fusion R Hang, Q Liu, H Song, Y Sun IEEE Transactions on Geoscience and Remote Sensing 54 (2), 783-794, 2015 | 80 | 2015 |
| Classification of hyperspectral images via multitask generative adversarial networks R Hang, F Zhou, Q Liu, P Ghamisi IEEE Transactions on Geoscience and Remote Sensing 59 (2), 1424-1436, 2020 | 51 | 2020 |
| Pyramid fully convolutional network for hyperspectral and multispectral image fusion F Zhou, R Hang, Q Liu, X Yuan IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 42 | 2019 |
| Robust matrix discriminative analysis for feature extraction from hyperspectral images R Hang, Q Liu, Y Sun, X Yuan, H Pei, J Plaza, A Plaza IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 34 | 2017 |
| Oceanic eddy identification using an AI scheme G Xu, C Cheng, W Yang, W Xie, L Kong, R Hang, F Ma, C Dong, J Yang Remote Sensing 11 (11), 1349, 2019 | 30 | 2019 |
| Hypergraph embedding for spatial-spectral joint feature extraction in hyperspectral images Y Sun, S Wang, Q Liu, R Hang, G Liu Remote Sensing 9 (5), 506, 2017 | 30 | 2017 |
| Adaptive deep pyramid matching for remote sensing scene classification Q Liu, R Hang, H Song, F Zhu, J Plaza, A Plaza arXiv preprint arXiv:1611.03589, 2016 | 30 | 2016 |
| Deep encoder-decoder networks for classification of hyperspectral and LiDAR data D Hong, L Gao, R Hang, B Zhang, J Chanussot IEEE Geoscience and Remote Sensing Letters, 2020 | 29 | 2020 |
| Graph regularized nonlinear ridge regression for remote sensing data analysis R Hang, Q Liu, H Song, Y Sun, F Zhu, H Pei IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2016 | 29 | 2016 |
| Nonlinear low-rank matrix completion for human motion recovery G Xia, H Sun, B Chen, Q Liu, L Feng, G Zhang, R Hang IEEE Transactions on Image Processing 27 (6), 3011-3024, 2018 | 28 | 2018 |
| Dimensionality reduction of hyperspectral image using spatial regularized local graph discriminant embedding R Hang, Q Liu IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018 | 26 | 2018 |
Qingshan LiuNanjing University of Information Science and Technology在 nuist.edu.cn 的电子邮件经过验证
