联系方式
lijing2017@cufe.edu.cn
毕业院校
2021.06毕业于中国人民公安大学，信息技术与网络安全学院，获工学博士学位
工作经历
2021.09 — 2023.12 太阳成集团tyc9728 讲师
2024.01— 至今 太阳成集团tyc9728 副教授
主讲课程
《数据挖掘与深度学习》、《人工智能基础与应用》、《Python程序设计》
研究方向
计算机视觉：多模态图像融合、目标识别、视频图像侦查等
遥感与地理信息系统：遥感图像处理、遥感应用、地理信息空间分析
学术成果
1.Jing Li,Yang B, Bai L, et al. TFIV: Multigrained Token Fusion for Infrared and Visible Image via Transformer[J]. IEEE Transactions on Instrumentation and Measurement, 2023.72.
2.Jing Li; Jianming Zhu; Chang Li; Xun Chen; Bin Yang; CGTF: Convolution-Guided Transformer for Infrared and Visible Image Fusion, IEEE Transactions on Instrumentation and Measurement, 2022, 71.
3. Jing Li; Hongtao Huo; Chang Li; Renhua Wang; Qi Feng; AttentionFGAN: Infrared and Visible Image Fusion Using Attention-Based Generative Adversarial Networks, IEEE Transactions on Multimedia, 2021, 23: 1383-1396. (ESI高被引)
4. Jing Li; Hongtao Huo; Chang Li; Renhua Wang; Chenhong Sui; Zhao Liu; Multi-grained Attention Network for Infrared and Visible Image Fusion, IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-12.
5. Yang, B., Mao, Y., Liu, L., Liu, X., Ma, Y., Li, J.（通讯作者）. From trained to untrained: A novel change detection framework using randomly initialized models with spatial–channel augmentation for hyperspectral images [J]. IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 1-14.
6.Jing Li; Hongtao Huo; Kejian Liu; Chang Li; Infrared and Visible Image Fusion Using Dual Discriminators Generative Adversarial Networks with Wasserstein Distance, Information Sciences, 2020, 529: 28-41.
7.Jing Li; Hongtao Huo*; Kejian Liu; Chang Li; Shuo Li; Xin Yang; Infrared and Visible Image Fusion via Multi-discriminators Wasserstein Generative Adversarial Network, 2019 18th IEEE International Conference on Machine Learning and Applications (ICMLA), Boca Raton, Florida, USA, 2019
科研项目
国家自然科学基金青年项目, 2023-2025, 主持；
高分辨率对地观测重大专项《高分公安XX应用示范系统》2015-2017，参与；
高分辨率对地观测重大专项《敏感地区XX技术研究》2018-2021，参与；
军民融合《XXX应用示范》2019-2021，参与；
公安部技术研究计划《无人区XX技术研究》2018-2020，参与；
