Pengda Qin

868 citations
14 papers · 455 indexed · h-index 9
Topics
Topic Modeling (9 papers)Natural Language Processing Techniques (7 papers)Advanced Image and Video Retrieval Techniques (3 papers)
Journals
NeurocomputingJournal of Control Science and EngineeringProceedings of the AAAI Conference on Artificial Intelligence

In The Last Decade

Pengda Qin

12 papers receiving 435 citations

Peers

Pengda Qin
Comparison fields: 5 of 55
  • Artificial Intelligence 370
  • Computer Vision and Pattern Recognition 94
  • Information Systems 41
  • Management Science and Operations Research 28
  • Signal Processing 17
Replace Mengting Hu with:
Mengting Hu China
Tengfei Liu China
Da Luo China
Zhixing Tan China
Weiqiang Jin China
Rong Xiao China
Weidi Xu China
Xinchi Chen China
Wenhan Xiong United States
Xuejie Zhang China
Pengda Qin relative to Mengting Hu China Mengting Hu's profile →
Citations per field
00.5×10×15×20×
Mengting Hu · 1×
Citations per year

Countries citing papers authored by Pengda Qin

Since Specialization
Citations

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

Fields of papers citing papers by Pengda Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengda Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Pengda Qin. A scholar is included among the top collaborators of Pengda Qin 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 Pengda Qin. Pengda Qin 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
#WorkIndexed citations
1 17
2 6
3 18
4 5
5 44
6 31
7 140
8 90
9 0
10 18
11 59
12 3
13 24
14 0

About Pengda Qin

Pengda Qin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology, having authored 14 papers that have together received 455 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (370 citations), Computer Vision and Pattern Recognition (94 citations) and General Social Sciences (9 citations). Pengda Qin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include William Yang Wang, Weiran Xu, Weiran Xu, Jun Guo, Wenhu Chen, Chunyun Zhang, Xin Wang, Ting Liu, Shaolei Wang and Qi Liu. Their work appears in journals such as Neurocomputing, Journal of Control Science and Engineering and Proceedings of the AAAI Conference on Artificial Intelligence.

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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