Ge Li

11.5k citations
259 papers · 5.3k · 3 hit papers · h-index 32

Impact in

Papers in

Ge Li

236 papers receiving 5.1k citations

Ge Li's Hit Papers

Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection 2019 · 391 citations
3910+3+7Years since publication100200300400

Peers

Ge Li
Comparison fields: 5 of 163
  • Computer Vision and Pattern Recognition 2.8k
  • Computer Graphics and Computer-Aided Design 281
  • Software 270
  • Artificial Intelligence 1.8k
  • Media Technology 421
Replace Xiaonan Luo with:
Xiaonan Luo China
Evangelos Milios Canada
Fazhi He China
James Philbin United States
Alan K. Mackworth Canada
Jun Wang China
Naveed Akhtar Australia
Xiao‐Yuan Jing China
Fei Wu China
Arthur C. Sanderson United States
Ge Li relative to Xiaonan Luo China Xiaonan Luo's profile →
Citations per field
00.5×4.7×
Xiaonan Luo · 1×
Citations per year

Countries citing papers authored by Ge Li

Since Specialization
Citations

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

Fields of papers citing papers by Ge Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ge Li, 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 Ge Li Line = papers co-authored together Ge Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 259 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths
Hit paper breakdown →
2015419
2
Graph Convolutional Label Noise Cleaner: Train a Plug-And-Play Action Classifier for Anomaly Detection
Hit paper breakdown →
2019391
3
Convolutional Neural Networks over Tree Structures for Programming Language Processing
Hit paper breakdown →
2016369
4 2019249
5 2017232
6 2016188
7 2018174
8 2021145
9 2016140
10 2019126
11 2020118
12 2021112
13 202289
14 201982
15 201878
16 201261
17 202161
18 202159
19 201557
20 202254

About Ge Li

Ge Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Computer Graphics and Computer-Aided Design and Environmental Engineering, having authored 259 papers that have together received 5.3k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (51 papers), Advanced Vision and Imaging (48 papers), Computer Graphics and Visualization Techniques (29 papers), Remote Sensing and LiDAR Applications (28 papers), Advanced Image and Video Retrieval Techniques (25 papers), Human Pose and Action Recognition (22 papers), Visual Attention and Saliency Detection (21 papers) and Topic Modeling (20 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.8k citations), Computer Graphics and Computer-Aided Design (281 citations), Software (270 citations), Artificial Intelligence (1.8k citations) and Media Technology (421 citations). Ge Li has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shan Liu, Thomas H. Li, Zhi Jin, Lili Mou, Yurui Ren, Wei Gao, Zhenqiang Ying, Jia-Xing Zhong, Yan Xu and Lu Zhang. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Multimedia, IEEE Transactions on Image Processing, Neurocomputing and IEEE Signal Processing Letters.

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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