1、J Wang, Wang J*, Li Y, et al. Automatic crack segmentation network based on large kernel pooling Transformer[J]. Advances in Structural Engineering, 2026, 28(1): 158-170.(SCI 4区) 2、Xiong B, Linyi L, Wang J*, et al. REM-Net: An Edge-Enhanced Network Integrating Transformer and State Space Models for Precise Pavement Crack Segmentation[J]. Construction and Building Materials, 2025, 512: 142216. (SCI 1区) 3、J Wang, Wang J, Li Y, et al. Crack segmentation network based on hybrid-window transformer and dual-branch fusion[J]. Applied Intelligence, 2025, 55(13): 944. (SCI 3区) 4、王建新,李林益,王进,等.基于频域Mamba与递归门控Transformer融合的路面裂缝分割方法[J/OL].中国公路学报,2025.1-17.https://link.cnki.net/urlid/61.1313.u.20250730.1311.002. 5、Hu S, Wu D, Wang J*, et al. The image super-resolution network based on dual-branch feature interaction attention mechanism[J]. The Visual Computer, 2025: 1-14.(SCI 3区) 6、Hu S, Huang S, Wang J*. Hybrid feature enhancement network for lightweight image super-resolution[J]. The Visual Computer, 2025: 1-13.(SCI 3区) 7、桂彦,叶文倩,王建新*,等.基于CNN和尺度自适应Transformer融合网络的路面裂缝分割方法[J].中国公路学报,2024,37(12):418-432.DOI:10.19721/j.cnki.1001-7372.2024.12.019. 8、Xiong B, Hong R, Wang J*, et al. DefNet: A multi-scale dual-encoding fusion network aggregating Transformer and CNN for crack segmentation[J]. Construction and Building Materials, 2024, 448: 138206. (SCI 1区) 9、Wang J, Zeng Z, Wang J*, et al. Automatic crack segmentation model based on multi-branch aggregation transformer[J]. Advances in Structural Engineering, 2024, 27(13): 2289-2302. (SCI 4区) 10、Wang J, Zou Y, Wu H. Image super-resolution method based on attention aggregation hierarchy feature[J]. The Visual Computer, 2023: 1-12. 10.1007/s00371-023-02968-x(SCI 3区) 11、Jianxin Wang, Yongsong Zou, Osama Alfarraj, Pradip Kumar Sharma, Wael Said, Jin Wang. Image Super-Resolution Method Based on the Interactive Fusion of Transformer and CNN Features[J]. The Visual Computer, 2023: 1-12. s00371-023-03138-9(SCI 3区) 12、王建新,吴宏林,张建明等.残差字典学习的快速图像超分辨率算法[J].计算机科学与探索,2018,12(08):1305-1314. (CSCD) |