ADASYN: Adaptive synthetic sampling approach for imbalanced learning H He, Y Bai, EA Garcia, S Li 2008 IEEE international joint conference on neural networks (IEEE world …, 2008 | 5182 | 2008 |
Image fusion with guided filtering S Li, X Kang, J Hu IEEE Transactions on Image processing 22 (7), 2864-2875, 2013 | 1791 | 2013 |
Deep learning for hyperspectral image classification: An overview S Li, W Song, L Fang, Y Chen, P Ghamisi, JA Benediktsson IEEE Transactions on Geoscience and Remote Sensing 57 (9), 6690-6709, 2019 | 1384 | 2019 |
Pixel-level image fusion: A survey of the state of the art S Li, X Kang, L Fang, J Hu, H Yin information Fusion 33, 100-112, 2017 | 1172 | 2017 |
Multifocus image fusion and restoration with sparse representation B Yang, S Li IEEE transactions on Instrumentation and Measurement 59 (4), 884-892, 2009 | 794 | 2009 |
Spectral–spatial hyperspectral image classification with edge-preserving filtering X Kang, S Li, JA Benediktsson IEEE transactions on geoscience and remote sensing 52 (5), 2666-2677, 2013 | 757 | 2013 |
Performance comparison of different multi-resolution transforms for image fusion S Li, B Yang, J Hu Information Fusion 12 (2), 74-84, 2011 | 703 | 2011 |
Recent advances on spectral–spatial hyperspectral image classification: An overview and new guidelines L He, J Li, C Liu, S Li IEEE Transactions on Geoscience and Remote Sensing 56 (3), 1579-1597, 2017 | 549 | 2017 |
Multifocus image fusion using region segmentation and spatial frequency S Li, B Yang Image and vision computing 26 (7), 971-979, 2008 | 546 | 2008 |
Combination of images with diverse focuses using the spatial frequency S Li, JT Kwok, Y Wang Information fusion 2 (3), 169-176, 2001 | 531 | 2001 |
Automatic segmentation of nine retinal layer boundaries in OCT images of non-exudative AMD patients using deep learning and graph search L Fang, D Cunefare, C Wang, RH Guymer, S Li, S Farsiu Biomedical optics express 8 (5), 2732-2744, 2017 | 520 | 2017 |
Hyperspectral image classification with deep feature fusion network W Song, S Li, L Fang, T Lu IEEE Transactions on Geoscience and Remote Sensing 56 (6), 3173-3184, 2018 | 495 | 2018 |
A new pan-sharpening method using a compressed sensing technique S Li, B Yang IEEE Transactions on Geoscience and Remote Sensing 49 (2), 738-746, 2010 | 465 | 2010 |
Fusing hyperspectral and multispectral images via coupled sparse tensor factorization S Li, R Dian, L Fang, JM Bioucas-Dias IEEE Transactions on Image Processing 27 (8), 4118-4130, 2018 | 456 | 2018 |
Pixel-level image fusion with simultaneous orthogonal matching pursuit B Yang, S Li Information fusion 13 (1), 10-19, 2012 | 438 | 2012 |
Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images S Li, JT Kwok, Y Wang Information Fusion 3 (1), 17-23, 2002 | 424 | 2002 |
Multifocus image fusion using artificial neural networks S Li, JT Kwok, Y Wang Pattern recognition letters 23 (8), 985-997, 2002 | 415 | 2002 |
Group-sparse representation with dictionary learning for medical image denoising and fusion S Li, H Yin, L Fang IEEE Transactions on biomedical engineering 59 (12), 3450-3459, 2012 | 410 | 2012 |
Classification of hyperspectral images by exploiting spectral–spatial information of superpixel via multiple kernels L Fang, S Li, W Duan, J Ren, JA Benediktsson IEEE transactions on geoscience and remote sensing 53 (12), 6663-6674, 2015 | 386 | 2015 |
Hyperspectral anomaly detection with attribute and edge-preserving filters X Kang, X Zhang, S Li, K Li, J Li, JA Benediktsson IEEE Transactions on Geoscience and Remote Sensing 55 (10), 5600-5611, 2017 | 373 | 2017 |