| MdedFusion: A multi-level detail enhancement decomposition method for infrared and visible image fusion H Tang, G Liu, L Tang, DP Bavirisetti, J Wang Infrared Physics & Technology 127, 104435, 2022 | 44 | 2022 |
| BTSFusion: Fusion of infrared and visible image via a mechanism of balancing texture and salience Y Qian, G Liu, H Tang, M Xing, R Chang Optics and Lasers in Engineering 173, 107925, 2024 | 20 | 2024 |
| Multi-level adaptive perception guidance based infrared and visible image fusion M Xing, G Liu, H Tang, Y Qian, J Zhang Optics and Lasers in Engineering 171, 107804, 2023 | 17 | 2023 |
| EgeFusion: Towards Edge Gradient Enhancement in Infrared and Visible Image Fusion With Multi-Scale Transform H Tang, G Liu, Y Qian, J Wang, J Xiong IEEE Transactions on Computational Imaging, 2024 | 16 | 2024 |
| DANT-GAN: A dual attention-based of nested training network for infrared and visible image fusion K Li, G Liu, X Gu, H Tang, J Xiong, Y Qian Digital Signal Processing 145, 104316, 2024 | 16 | 2024 |
| MPCFusion: Multi-scale parallel cross fusion for infrared and visible images via convolution and vision Transformer H Tang, Y Qian, M Xing, Y Cao, G Liu Optics and Lasers in Engineering 176, 108094, 2024 | 7 | 2024 |
| CFNet: An infrared and visible image compression fusion network M Xing, G Liu, H Tang, Y Qian, J Zhang Pattern Recognition 156, 110774, 2024 | 5 | 2024 |
| LiMFusion: Infrared and visible image fusion via local information measurement Y Qian, H Tang, G Liu, M Xing, G Xiao, DP Bavirisetti Optics and Lasers in Engineering 181, 108435, 2024 | 4 | 2024 |
| GAN-GA: infrared and visible image fusion generative adversarial network based on global awareness J Wu, G Liu, X Wang, H Tang, Y Qian Applied Intelligence, 1-21, 2024 | 4 | 2024 |
| R2F-UGCGAN: a regional fusion factor-based union gradient and contrast generative adversarial network for infrared and visible image fusion Y Xie, G Liu, R Xu, DP Bavirisetti, H Tang, M Xing Journal of Modern Optics 70 (1), 52-68, 2023 | 4 | 2023 |
| MRASFusion: A multi-scale residual attention infrared and visible image fusion network based on semantic segmentation guidance R An, G Liu, Y Qian, M Xing, H Tang Infrared Physics & Technology 139, 105343, 2024 | 3 | 2024 |
| SeGFusion: A semantic saliency guided infrared and visible image fusion method J Xiong, G Liu, H Tang, X Gu, DP Bavirisetti Infrared Physics & Technology 140, 105344, 2024 | 2 | 2024 |
| GDNet: a low-light image enhancement network based on Ghost-Block and unique image decomposition R Chang, G Liu, Y Qian, H Tang, G Wang, DP Bavirisetti The Journal of Supercomputing 81 (1), 1-27, 2025 | | 2025 |
| FusionNGFPE: An image fusion approach driven by non-global fuzzy pre-enhancement framework X Zhang, G Liu, M Li, Q Ren, H Tang, DP Bavirisetti Digital Signal Processing 156, 104801, 2025 | | 2025 |
| RSTFusion: an end-to-end fusion network for infrared and visible images based on residual swin transfomer K Li, H Tang, G Liu, R Chang, M Xing, J Tang Neural Computing and Applications, 1-23, 2024 | | 2024 |
| RDGMEF: a multi-exposure image fusion framework based on Retinex decompostion and guided filter R Chang, G Liu, H Tang, Y Qian, J Tang Neural Computing and Applications, 1-20, 2024 | | 2024 |
| Environment enhanced fusion of infrared and visible images based on saliency assignment J Wang, G Liu, X Zhang, H Tang Signal, Image and Video Processing 18 (2), 1443-1453, 2024 | | 2024 |
Gang LiuShanghai University of Electrical PowerBestätigte E-Mail-Adresse bei shiep.edu.cn