Ling-Hao Han

1.0k total citations · 2 hit papers
10 papers, 586 citations indexed

About

Ling-Hao Han is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Ling-Hao Han has authored 10 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 2 papers in Artificial Intelligence and 2 papers in Media Technology. Recurrent topics in Ling-Hao Han's work include Advanced Image Processing Techniques (4 papers), Advanced Vision and Imaging (3 papers) and Image Enhancement Techniques (3 papers). Ling-Hao Han is often cited by papers focused on Advanced Image Processing Techniques (4 papers), Advanced Vision and Imaging (3 papers) and Image Enhancement Techniques (3 papers). Ling-Hao Han collaborates with scholars based in China, Singapore and United Kingdom. Ling-Hao Han's co-authors include Chunle Guo, Chongyi Li, Ming‐Ming Cheng, Chen Change Loy, Jun Jiang, Jinwei Gu, Zhi Chai, Xin Jin, Weidong Zhang and Qibin Hou and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and arXiv (Cornell University).

In The Last Decade

Ling-Hao Han

10 papers receiving 568 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Low-Light Image and Video Enhancement Using Deep Learning: A Survey

2021 348 citations Chongyi Li, Chunle Guo et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →
Underwater Ranker: Learn Which Is Better and How to Be Better

2023 112 citations Chunle Guo, Xin Jin et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ling-Hao Han China	7	530	177	54	31	21	10	586
Shuzhou Yang China	8	584 1.1×	197 1.1×	31 0.6×	17 0.5×	39 1.9×	9	649
Akshay Dudhane India	16	702 1.3×	219 1.2×	98 1.8×	20 0.6×	10 0.5×	29	782
Prashant W. Patil India	16	532 1.0×	131 0.7×	46 0.9×	17 0.5×	9 0.4×	27	571
Jiandong Tian China	9	320 0.6×	98 0.6×	18 0.3×	42 1.4×	7 0.3×	39	384
Xiaojie Chu United States	5	399 0.8×	164 0.9×	39 0.7×	29 0.9×	4 0.2×	7	493
Hui Qian China	8	539 1.0×	261 1.5×	42 0.8×	16 0.5×	4 0.2×	17	618
Zhiying Jiang China	11	838 1.6×	462 2.6×	31 0.6×	77 2.5×	42 2.0×	41	992
Kunqian Li China	13	872 1.6×	312 1.8×	25 0.5×	29 0.9×	72 3.4×	41	958
Rajeev Yasarla United States	10	543 1.0×	187 1.1×	47 0.9×	14 0.5×	4 0.2×	19	620

Countries citing papers authored by Ling-Hao Han

Since Specialization

Citations

This map shows the geographic impact of Ling-Hao Han's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ling-Hao Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling-Hao Han more than expected).

Fields of papers citing papers by Ling-Hao Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling-Hao Han. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ling-Hao Han. The network helps show where Ling-Hao Han may publish in the future.

Co-authorship network of co-authors of Ling-Hao Han

This figure shows the co-authorship network connecting the top 25 collaborators of Ling-Hao Han. A scholar is included among the top collaborators of Ling-Hao Han based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ling-Hao Han. Ling-Hao Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Cheng, Ming‐Ming, Peng-Tao Jiang, Ling-Hao Han, Liang Wang, & Philip H. S. Torr. (2023). Deeply Explain CNN Via Hierarchical Decomposition. International Journal of Computer Vision. 131(5). 1091–1105. 10 indexed citations

2.

Guo, Chunle, Xin Jin, Ling-Hao Han, et al.. (2023). Underwater Ranker: Learn Which Is Better and How to Be Better. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 702–709. 112 indexed citations breakdown →

3.

Jin, Xin, Ling-Hao Han, Chunle Guo, et al.. (2023). Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising. 13229–13238. 12 indexed citations

4.

Han, Ling-Hao, et al.. (2023). DNF: Decouple and Feedback Network for Seeing in the Dark. 18135–18144. 28 indexed citations

5.

Li, Zhen, et al.. (2023). AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation. 9801–9810. 19 indexed citations

6.

Zheng, Lin, Zhao Zhang, Ling-Hao Han, & Shao-Ping Lu. (2022). Multi-Mode Interactive Image Segmentation. Proceedings of the 30th ACM International Conference on Multimedia. 905–914. 5 indexed citations

7.

Li, Chongyi, Chunle Guo, Ling-Hao Han, et al.. (2021). Lighting the Darkness in the Deep Learning Era.. arXiv (Cornell University). 4 indexed citations

8.

Li, Chongyi, Chunle Guo, Ling-Hao Han, et al.. (2021). Low-Light Image and Video Enhancement Using Deep Learning: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(12). 9396–9416. 348 indexed citations breakdown →

9.

Jiang, Peng-Tao, Ling-Hao Han, Qibin Hou, Ming‐Ming Cheng, & Yunchao Wei. (2021). Online Attention Accumulation for Weakly Supervised Semantic Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(10). 7062–7077. 47 indexed citations

10.

Liu, Yuanhao, et al.. (2019). The Moving Target Recognition and Tracking Using RGB-D Data with the Mobile Robot. 4342–4347. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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