Jing Li

According to our database, Jing Li authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification.

Lu Bai, Lixin Cui, Yue Wang, Ming Li, Jing Li, Philip S. Yu, Edwin R. Hancock

IEEE Trans. Knowl. Data Eng., November, 2024

CEFusion: An Infrared and Visible Image Fusion Network Based on Cross-Modal Multi-Granularity Information Interaction and Edge Guidance.

Bin Yang, Yuxuan Hu, Xiaowen Liu, Jing Li

IEEE Trans. Intell. Transp. Syst., November, 2024

RdmkNet & Toronto-RDMK: Large-Scale Datasets for Road Marking Classification and Segmentation.

Jing Du, Lingfei Ma, Jing Li, Nannan Qin, John S. Zelek, Haiyan Guan, Jonathan Li

IEEE Trans. Intell. Transp. Syst., October, 2024

QBER: Quantum-based Entropic Representations for un-attributed graphs.

Lixin Cui, Ming Li, Lu Bai, Yue Wang, Jing Li, Yanchao Wang, Zhao Li, Yunwen Chen, Edwin R. Hancock

Pattern Recognit., January, 2024

Dual-modal Prior Semantic Guided Infrared and Visible Image Fusion for Intelligent Transportation System.

Jing Li, Lu Bai, Bin Yang, Chang Li, Lingfei Ma, Lixin Cui, Edwin R. Hancock

CoRR, 2024

2023

TFIV: Multigrained Token Fusion for Infrared and Visible Image via Transformer.

Jing Li, Bin Yang, Lu Bai, Hao Dou, Chang Li, Lingfei Ma

IEEE Trans. Instrum. Meas., 2023

From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial-Channel Augmentation for Hyperspectral Images.

Bin Yang, Yin Mao, Licheng Liu, Xinxin Liu, Yuzhong Ma, Jing Li

IEEE Trans. Geosci. Remote. Sens., 2023

Graph Representation Learning for Infrared and Visible Image Fusion.

Jing Li, Lu Bai, Bin Yang, Chang Li, Lingfei Ma, Edwin R. Hancock

CoRR, 2023

Enhancing Spatial Resolution of Building Datasets Using Transformer-Based Single-Image Super-Resolution.

Yuwei Cai, Hongjie He, Zhimeng He, Michael A. Chapman, Jing Li, Lingfei Ma, Jonathan Li

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022

CGTF: Convolution-Guided Transformer for Infrared and Visible Image Fusion.

Jing Li, Jianming Zhu, Chang Li, Xun Chen, Bin Yang

IEEE Trans. Instrum. Meas., 2022

DSG-Fusion: Infrared and visible image fusion via generative adversarial networks and guided filter.

Xin Yang, Hongtao Huo, Jing Li, Chang Li, Zhao Liu, Xun Chen

Expert Syst. Appl., 2022

An Attention-Guided and Wavelet-Constrained Generative Adversarial Network for Infrared and Visible Image Fusion.

Xiaowen Liu, Renhua Wang, Hongtao Huo, Xin Yang, Jing Li

CoRR, 2022

2021

AttentionFGAN: Infrared and Visible Image Fusion Using Attention-Based Generative Adversarial Networks.

Jing Li, Hongtao Huo, Chang Li, Renhua Wang, Qi Feng

IEEE Trans. Multim., 2021

Multigrained Attention Network for Infrared and Visible Image Fusion.

Jing Li, Hongtao Huo, Chang Li, Renhua Wang, Chenhong Sui, Zhao Liu

IEEE Trans. Instrum. Meas., 2021

2020

Infrared and visible image fusion using dual discriminators generative adversarial networks with Wasserstein distance.

Jing Li, Hongtao Huo, Kejian Liu, Chang Li

Inf. Sci., 2020

2019

Poisson Reconstruction-Based Fusion of Infrared and Visible Images via Saliency Detection.

Jing Li, Hongtao Huo, Chenhong Sui, Chenchen Jiang, Chang Li

IEEE Access, 2019

Infrared and Visible Image Fusion via Multi-discriminators Wasserstein Generative Adversarial Network.

Jing Li, Hongtao Huo, Kejian Liu, Chang Li, Shuo Li, Xin Yang

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019