江结林，南京信息工程大学副教授，硕士生导师。2015年11月毕业于南京理工大学计算机科学与工程学院，获工学博士学位。2014年7月至2017年7月于香港理工大学做研究助理及博士后。主要研究方向为：疵点检测、图像分类、图像复原等。主持国家级、省级项目等5项，参编《计算思维导论》教材1部。

Selected Publications over three years：（# co-first author，*Corresponding author）

[1] S. Wei, J. Jiang*, X. Xu. UniNet: A contrastive learning-guided unified framework with feature selection for anomaly detection. In Proceedings of the IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR), 2025.

[2] J. Jiang, X. Liu, P. Yan, S. Wei, Y Cui. Localize-Diffusion Based Dual-Branch Anomaly Detection, Neural Networks, 2025.

 [3] J. Jiang, S. Wei, X. Xu, Y. Cui, X. Liu. Unsupervised Anomaly Detection and Localization based on Two-Hierarchy Normalizing Flow, IEEE Transactions on Instrumentation & Measurement, vol. 73, 2024.

[4] J. Zhu#, P. Yan#, J. Jiang*, Y. Cui and X. Xu. Asymmetric Teacher-Student Feature Pyramid Matching for Industrial Anomaly Detection. IEEE Transactions on Instrumentation & Measurement, vol. 73, 2024.

[5] J. Jiang et al., Masked swin transformer Unet for industrial anomaly detection, IEEE Transactions on Industrial Informatics, vol. 19, no.2, pp. 2200-2209, 2023.

[6] J. Jiang, H. Xu, X. Xu , Y Cui , J. Wu, Transformer-based fused attention combined with CNNs for image classiffcation, Neural Processing Letters, vol. 55,  pp. 11905-11919, 2023.

[7]J. Jiang, K. Yang, X. Xu and Y. Cui, A serial attention module-based deep convolutional neural network for mixed  Gaussian-impulse  removal, IET Image Process, vol. 17, no. 6, pp. 1837-1851, 2023.

[8] J. Jiang, J. Guo, M. Khan, Y. Cui, W. Lin, Energy-saving service offloading for the internet of medical things using deep reinforcement learning. ACM Transactions on Sensor Networks, vol. 19, no. 23, pp. 1-20, 2023.

[9] J. Jiang, X. Hong, Y. Zhao, X. Xu, Y. Cui，SDAUNet: A simple dual attention mechanism UNet for mixed noise removal, IET Image Process, vol. 17, no. 13, pp. 1837-1851, 2023.

[10] J. Jiang, L. Liu, Y. Cui and Y. Zhao, A nested UNet based on multi-scale feature extraction for mixed Gaussian-impulse removal, Applied Sciences, vol. 13, no. 17, 9520, 2023.

发明专利：

1.江结林，朱加乐，郭浩然。一种基于Swin Transformer结构结合SSIM和GMSD的疵点检测方法。专利号：ZL 2022 1 0535974.4

2.江结林，刘西应，许小龙，吴金涛，赵英男. 一种异常图像样本生成方法及装置。专利号：ZL 2023 1 0621436.1

3. 江结林，史明月，刘西应，陈亚当，赵英男。一种多尺度互补学习的图像去噪方法及装置。专利号：ZL 2023 1 1832535.0 

4. 江结林，刘西应，陈亚当，魏顺，许小龙。 基于距离信息驱动的复杂工业图像异常检测方法及装置。专利号：ZL 2024 1 0438275.7 

5.江结林，孙晋开，刘西应，许小龙，陈亚当。一种双阶段图像的异常检测与重构方法及系统。专利号：ZL 2024 1 0227319.1

6.江结林，魏顺，刘西应，许小龙，吴金涛。一种工业异常检测方法及系统。专利号：ZL 2024 1 0925191.6 

7. 朱加乐，江结林，陈亚当，金子龙。一种基于yolov5和注意力机制模型的疵点检测方法。专利号：ZL 2021 1 1316595.8   

8. 胡祥奔，江结林，胡志臣，许小龙。一种面向文献的表格信息抽取方法。专利号：ZL 2021 1 0736883.2

9. 唐柏轩，江结林，胡志臣，许小龙。一种基于LSD线段检测的文档图像三角图检测方法。专利号：ZL 2021 1 1175439.4