Lin Meng

3.3k total citations · 1 hit paper
185 papers, 2.1k citations indexed

About

Lin Meng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Lin Meng has authored 185 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Computer Vision and Pattern Recognition, 40 papers in Artificial Intelligence and 22 papers in Computer Networks and Communications. Recurrent topics in Lin Meng's work include Handwritten Text Recognition Techniques (25 papers), Advanced Neural Network Applications (21 papers) and Image Processing and 3D Reconstruction (19 papers). Lin Meng is often cited by papers focused on Handwritten Text Recognition Techniques (25 papers), Advanced Neural Network Applications (21 papers) and Image Processing and 3D Reconstruction (19 papers). Lin Meng collaborates with scholars based in Japan, China and United States. Lin Meng's co-authors include Hengyi Li, Xuebin Yue, Hiroyuki Tomiyama, Zhuo Li, Xiangbo Kong, Feng Zeng, Jinsong Wu, Zhichen Wang, Keith Marzullo and Yangyang Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Lin Meng

161 papers receiving 2.0k citations

Hit Papers

Model Compression for Deep Neural Networks: A Survey 2023 2026 2024 2025 2023 40 80 120
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.

  1. Model Compression for Deep Neural Networks: A Survey
    2023 126 citations Zhuo Li, Hengyi Li et al. Computers profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lin Meng Japan 23 735 457 368 212 207 185 2.1k
Anupam Shukla India 27 879 1.2× 615 1.3× 395 1.1× 237 1.1× 161 0.8× 170 2.1k
Kai Huang China 29 642 0.9× 368 0.8× 690 1.9× 713 3.4× 427 2.1× 336 3.6k
Debnath Bhattacharyya India 29 584 0.8× 439 1.0× 272 0.7× 162 0.8× 113 0.5× 229 2.4k
Hanxiang Wang China 24 567 0.8× 437 1.0× 123 0.3× 204 1.0× 212 1.0× 74 2.7k
Muhammad Awais Pakistan 24 323 0.4× 311 0.7× 278 0.8× 416 2.0× 153 0.7× 112 1.9k
Douglas Creighton Australia 24 771 1.0× 578 1.3× 64 0.2× 314 1.5× 161 0.8× 97 2.5k
Di Liu China 26 404 0.5× 308 0.7× 565 1.5× 289 1.4× 163 0.8× 209 2.2k
Sidan Du China 24 644 0.9× 414 0.9× 305 0.8× 171 0.8× 314 1.5× 115 2.0k
Christos‐Nikolaos Anagnostopoulos Greece 24 1.5k 2.0× 510 1.1× 85 0.2× 122 0.6× 70 0.3× 158 3.0k
Yan Wu China 23 626 0.9× 391 0.9× 63 0.2× 235 1.1× 171 0.8× 231 2.4k

Countries citing papers authored by Lin Meng

Since Specialization
Citations

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

Fields of papers citing papers by Lin Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lin Meng

This figure shows the co-authorship network connecting the top 25 collaborators of Lin Meng. A scholar is included among the top collaborators of Lin Meng 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 Lin Meng. Lin Meng 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.
Meng, Lin, et al.. (2025). Automatic pruning rate adjustment for dynamic token reduction in vision transformer. Applied Intelligence. 55(5). 2 indexed citations
2.
Sun, Guangyi, Hongxing Liu, Leihua Weng, et al.. (2025). A brain-computer interface roadmap for diagnosing and treating neurological disorders. 1(1). 100016–100016.
3.
Yang, Banghua, et al.. (2025). STA-Net: Spatial–temporal alignment network for hybrid EEG-fNIRS decoding. Information Fusion. 119. 103023–103023. 5 indexed citations
4.
Yang, Yihong, et al.. (2025). Dependency-Aware Online Microservice Re-Scheduling for Adaptive Resources Co-Optimization in Edge Networks. IEEE Transactions on Services Computing. 18(6). 3649–3667.
5.
Wang, Yan, et al.. (2025). DC-PFL: A dynamic clustering-based personalized federated learning method for human activity recognition. Engineering Science and Technology an International Journal. 72. 102230–102230.
6.
7.
Chen, Keke, Yixuan Wang, Mengyue Wang, et al.. (2024). Rehabilitation Response in Tremor‐ and Non‐Tremor‐Dominant Parkinson Disease: A Task‐fMRI Study. Brain and Behavior. 14(10). e70102–e70102.
8.
Li, Zhuo, et al.. (2024). Deep learning-driven digital twin-enabled smart monitoring system. Procedia Computer Science. 246. 353–361. 1 indexed citations
9.
Li, Zhuo, et al.. (2023). IoT-based automatic deep learning model generation and the application on Empty-dish Recycling Robots. Internet of Things. 25. 101047–101047. 12 indexed citations
10.
Li, Hengyi, et al.. (2023). Deep Learning Architecture Improvement Based on Dynamic Pruning and Layer Fusion. Electronics. 12(5). 1208–1208. 6 indexed citations
11.
Li, Zhuo, Hengyi Li, & Lin Meng. (2023). Model Compression for Deep Neural Networks: A Survey. Computers. 12(3). 60–60. 126 indexed citations breakdown →
12.
Meng, Lin, et al.. (2023). IoT-based dataset augmentation method for oracle bone inscriptions reorganisation. International Journal of Advanced Mechatronic Systems. 10(2). 102–111. 1 indexed citations
13.
14.
Li, Hengyi, et al.. (2023). A Transformer-Based Neural Network for Gait Prediction in Lower Limb Exoskeleton Robots Using Plantar Force. Sensors. 23(14). 6547–6547. 11 indexed citations
15.
Zhang, Yongqing, et al.. (2022). A hybrid ensemble and evolutionary algorithm for imbalanced classification and its application on bioinformatics. Computational Biology and Chemistry. 98. 107646–107646. 3 indexed citations
16.
Yue, Xuebin, et al.. (2022). YOLO-GG: a slight object detection model for empty-dish recycling robot. 6. 59–63. 5 indexed citations
17.
18.
Zhang, Le, Zhichen Wang, Lei Wang, et al.. (2021). Machine learning-based real-time visible fatigue crack growth detection. Digital Communications and Networks. 7(4). 551–558. 65 indexed citations
19.
20.
Li, Xiang, et al.. (2018). Study on Mangrove Species Classification based on ZY-3 Image. Yaogan jishu yu yingyong. 33(2). 360–369. 3 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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