Chen Lin

617 citations
32 papers · 364 indexed · h-index 11

Impact in

Papers in

    • Domain Adaptation and Few-Shot Learning 8
    • Text and Document Classification Technologies 3
    • Anomaly Detection Techniques and Applications 3
    • Face and Expression Recognition 3
    • Advanced Neural Network Applications 3
    • Multimodal Machine Learning Applications 3

Chen Lin

30 papers receiving 349 citations

Peers

Chen Lin
Comparison fields: 5 of 81
  • Computer Science Applications 27
  • Cancer Research 75
  • Artificial Intelligence 151
  • Computer Vision and Pattern Recognition 81
  • Media Technology 27
Replace Kun Lan with:
Kun Lan China
Christoph Baur Germany
Hongbo Du United Kingdom
Luxin Zhang China
Yuan‐chin Ivan Chang Taiwan
Murtada K. Elbashir Saudi Arabia
Xinguang Xiang China
Quande Liu Hong Kong
Chen Lin relative to Kun Lan China Kun Lan's profile →
Citations per field
00.5×5.8×
Kun Lan · 1×
Citations per year

Countries citing papers authored by Chen Lin

Since Specialization
Citations

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

Fields of papers citing papers by Chen Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Chen Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chen Lin Line = papers co-authored together Chen Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201570
2 201951
3 201833
4 201829
5 202026
6 201721
7 200518
8 202117
9 201914
10 202312
11 202411
12 20179
13 20239
14 20238
15 20185
16
WIM at TREC 2005.
20053
17 20193
18 20053
19 20193
20 20213

About Chen Lin

Chen Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 32 papers that have together received 364 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (8 papers), Face and Expression Recognition (3 papers), Text and Document Classification Technologies (3 papers), Advanced Neural Network Applications (3 papers), Anomaly Detection Techniques and Applications (3 papers), Multimodal Machine Learning Applications (3 papers), Cancer-related molecular mechanisms research (3 papers) and Remote-Sensing Image Classification (3 papers). The work is most often cited by research in Computer Science Applications (27 citations), Cancer Research (75 citations), Artificial Intelligence (151 citations), Computer Vision and Pattern Recognition (81 citations) and Media Technology (27 citations). Chen Lin has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Rui Wang, Yali Cao, Jianguo Shao, Min Chi, Yundong Li, Yew-Soon Ong, Dahua Lin, Xin Yuan, Ivor W. Tsang and Qinghua Zheng. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access, Machine Learning, Tumor Biology and IEEE Transactions on Neural Networks and Learning Systems.

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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