Shaohui Lin

3.6k total citations · 2 hit papers
62 papers, 2.1k citations indexed

About

Shaohui Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Shaohui Lin has authored 62 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 6 papers in Control and Systems Engineering. Recurrent topics in Shaohui Lin's work include Advanced Neural Network Applications (13 papers), Image and Signal Denoising Methods (10 papers) and Human Pose and Action Recognition (10 papers). Shaohui Lin is often cited by papers focused on Advanced Neural Network Applications (13 papers), Image and Signal Denoising Methods (10 papers) and Human Pose and Action Recognition (10 papers). Shaohui Lin collaborates with scholars based in China, United States and Sweden. Shaohui Lin's co-authors include Rongrong Ji, Lizhuang Ma, Yanyun Qu, Yuan Xie, Zhizhong Zhang, Feiyue Huang, Baochang Zhang, Ruizhi Qiao, Haiyan Wu and Jian Zhou and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Shaohui Lin

53 papers receiving 2.0k citations

Hit Papers

Contrastive Learning for Compact Single Image Dehazing 2019 2026 2021 2023 2021 2019 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shaohui Lin China 17 1.6k 791 325 155 115 62 2.1k
Christian Leistner Austria 20 2.0k 1.3× 524 0.7× 375 1.2× 111 0.7× 54 0.5× 35 2.4k
Yibing Song China 22 2.1k 1.3× 456 0.6× 353 1.1× 73 0.5× 35 0.3× 53 2.5k
Margret Keuper Germany 11 2.3k 1.4× 430 0.5× 304 0.9× 59 0.4× 39 0.3× 35 2.6k
Xinge You China 21 907 0.6× 355 0.4× 254 0.8× 93 0.6× 50 0.4× 52 1.3k
Caner Hazırbaş Germany 9 2.6k 1.6× 430 0.5× 377 1.2× 145 0.9× 78 0.7× 14 3.1k
Sajid Javed United Arab Emirates 18 1.3k 0.8× 435 0.5× 217 0.7× 110 0.7× 46 0.4× 91 1.9k
Zhenyu He China 19 1.1k 0.7× 242 0.3× 222 0.7× 167 1.1× 50 0.4× 40 1.4k
Huanqiang Zeng China 29 2.2k 1.4× 267 0.3× 545 1.7× 95 0.6× 69 0.6× 157 2.6k
Vishnu Naresh Boddeti United States 21 828 0.5× 630 0.8× 87 0.3× 103 0.7× 37 0.3× 58 1.5k

Countries citing papers authored by Shaohui Lin

Since Specialization
Citations

This map shows the geographic impact of Shaohui Lin'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 Shaohui Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaohui Lin more than expected).

Fields of papers citing papers by Shaohui Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaohui Lin. 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 Shaohui Lin. The network helps show where Shaohui Lin may publish in the future.

Co-authorship network of co-authors of Shaohui Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Shaohui Lin. A scholar is included among the top collaborators of Shaohui Lin 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 Shaohui Lin. Shaohui Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Wei, et al.. (2025). LIPT: Latency-Aware Image Processing Transformer. IEEE Transactions on Image Processing. 34. 3056–3069.
2.
Li, Wei, et al.. (2025). Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution. IEEE Transactions on Image Processing. 34. 8461–8473.
3.
Zhao, Zhengyan, et al.. (2025). Numerical Simulation Study on Internal Flow Law and Efficiency of Gas-Liquid Mixed Jet Pump. Processes. 13(2). 495–495.
5.
Wang, Runqi, et al.. (2025). SET: Spectral Enhancement for Tiny Object Detection. 4713–4723. 1 indexed citations
6.
Dong, Wenhao, Shaohui Lin, Xiaoyan Luo, et al.. (2025). Fusion-Mamba for Cross-Modality Object Detection. IEEE Transactions on Multimedia. 27. 7392–7406. 7 indexed citations
7.
Zhang, Zhizhong, Yuan Xie, Yanbo Wang, et al.. (2024). Dynamic image super-resolution via progressive contrastive self-distillation. Pattern Recognition. 153. 110502–110502. 3 indexed citations
8.
Chen, Fuhai, et al.. (2024). SegCFT: Context-aware Fourier Transform for efficient semantic segmentation. Neurocomputing. 596. 127946–127946. 3 indexed citations
9.
Wei, Kai, Hongyan Wang, Junjie Yang, Shaohui Lin, & Chunbo Li. (2024). Nutritional risk and adverse health outcomes in Chinese community-dwelling older adults: A study based on the Elderly Nutritional Indicators for Geriatric Malnutrition Assessment (ENIGMA). Nutrition. 126. 112489–112489. 2 indexed citations
10.
Wei, Kai, Shaohui Lin, Junjie Yang, & Chunbo Li. (2024). Dietary Habits and Depression in Community-Dwelling Chinese Older Adults: Cross-Sectional Analysis of the Moderating Role of Physical Exercise. Nutrients. 16(5). 740–740. 2 indexed citations
11.
Shen, Yunhang, et al.. (2024). Weakly Supervised Open-Vocabulary Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3404–3412. 8 indexed citations
12.
Lin, Shaohui, et al.. (2024). Kumaraswamy Wavelet for Heterophilic Scene Graph Generation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 1138–1146. 1 indexed citations
13.
Lin, Shaohui, et al.. (2023). Improving rare relation inferring for scene graph generation using bipartite graph network. Computer Vision and Image Understanding. 239. 103901–103901. 2 indexed citations
14.
Lin, Shaohui, et al.. (2023). Hybrid knowledge distillation from intermediate layers for efficient Single Image Super-Resolution. Neurocomputing. 554. 126592–126592. 11 indexed citations
15.
Lin, Shaohui, et al.. (2023). Explicit Invariant Feature Induced Cross-Domain Crowd Counting. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 259–267. 3 indexed citations
16.
Shen, Yunhang, et al.. (2023). THANet: Transferring Human Pose Estimation to Animal Pose Estimation. Electronics. 12(20). 4210–4210. 6 indexed citations
17.
Lin, Shaohui, Rongrong Ji, Yuchao Li, Cheng Deng, & Xuelong Li. (2019). Toward Compact ConvNets via Structure-Sparsity Regularized Filter Pruning. IEEE Transactions on Neural Networks and Learning Systems. 31(2). 574–588. 134 indexed citations
18.
Li, Yuchao, Rongrong Ji, Shaohui Lin, et al.. (2019). Dynamic Neural Network Decoupling.. arXiv (Cornell University). 3 indexed citations
19.
Gao, Qinquan, et al.. (2017). FZUImageReg: A toolbox for medical image registration and dose fusion in cervical cancer radiotherapy. PLoS ONE. 12(4). e0174926–e0174926. 2 indexed citations
20.
Lin, Shaohui, Rongrong Ji, Xiaowei Guo, & Xuelong Li. (2016). Towards convolutional neural networks compression via global error reconstruction. Institutional Repository of Xi'an Institute of Optics and Fine Mechanics, Chinese Academy of Sciences (Xian Institute of Optics and Precision Mechanics). 1753–1759. 30 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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