Dian Li

967 total citations · 1 hit paper
14 papers, 599 citations indexed

About

Dian Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Dian Li has authored 14 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Signal Processing. Recurrent topics in Dian Li's work include Multimodal Machine Learning Applications (7 papers), Human Pose and Action Recognition (6 papers) and Video Analysis and Summarization (4 papers). Dian Li is often cited by papers focused on Multimodal Machine Learning Applications (7 papers), Human Pose and Action Recognition (6 papers) and Video Analysis and Summarization (4 papers). Dian Li collaborates with scholars based in China, Malaysia and United States. Dian Li's co-authors include Fan Yin, Xiangju Lu, Yuanliu Liu, Zhanyu Wang, Zhenhua Liu, Xiu Li, Ying Shan, Yixiao Ge, Xiaohu Qie and Xihui Liu and has published in prestigious journals such as IEEE Transactions on Multimedia, Journal of the Indian Society of Remote Sensing and Journal of Image and Graphics.

In The Last Decade

Dian Li

11 papers receiving 582 citations

Hit Papers

Video-based emotion recognition using CNN-RNN and C3D hyb... 2016 2026 2019 2022 2016 100 200 300

Peers

Dian Li
Comparison fields: 5 of 75
  • Computer Vision and Pattern Recognition 440
  • Experimental and Cognitive Psychology 241
  • Artificial Intelligence 161
  • Signal Processing 81
  • Cognitive Neuroscience 44
Xiangju Lu China
Yuanliu Liu China
Min Peng China
Yante Li Finland
Zhanpeng Zhang China
Guanming Lu China
Anh Cat Le Ngo Malaysia
Ciprian Corneanu Spain
Dae Hoe Kim South Korea
Xiangju Lu China View profile →
Citations per field, relative to Dian Li
Dian Li · 1×
Citations per year, relative to Dian Li
Dian Li · 1×

Countries citing papers authored by Dian Li

Since Specialization
Citations

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

Fields of papers citing papers by Dian Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dian Li

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

All Works

14 of 14 papers shown
# Work Indexed citations
1 0
2 3
3 0
4 2
5 0
6 5
7 2
8 4
9 82
10 26
11 2
12 84
13 21
14
Video-based emotion recognition using CNN-RNN and C3D hybrid networks breakdown →
368

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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