Pengpeng Zeng

889 citations
32 papers · 534 indexed · h-index 14
Topics
Multimodal Machine Learning Applications (29 papers)Advanced Image and Video Retrieval Techniques (20 papers)Domain Adaptation and Few-Shot Learning (11 papers)

In The Last Decade

Pengpeng Zeng

30 papers receiving 533 citations

Peers

Pengpeng Zeng
Comparison fields: 5 of 38
  • Computer Vision and Pattern Recognition 489
  • Artificial Intelligence 265
  • Information Systems 7
  • Signal Processing 7
  • Computational Mechanics 6
Replace Alyssa Mensch with:
Alyssa Mensch United States
Yuyu Guo China
Rakshith Shetty Germany
Jiabo Ye China
Anand Mishra India
Chenglin Wu China
Nicholas FitzGerald United States
Leigang Qu China
Difei Gao Singapore
Pengpeng Zeng relative to Alyssa Mensch United States Alyssa Mensch's profile →
Citations per field
00.5×10×15×21.8×
Alyssa Mensch · 1×
Citations per year

Countries citing papers authored by Pengpeng Zeng

Since Specialization
Citations

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

Fields of papers citing papers by Pengpeng Zeng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengpeng Zeng

This figure shows the co-authorship network connecting the top 25 collaborators of Pengpeng Zeng. A scholar is included among the top collaborators of Pengpeng Zeng 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 Pengpeng Zeng. Pengpeng Zeng 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
#WorkIndexed citations
1 0
2 0
3 1
4 4
5 11
6 2
7 1
8 20
9 18
10 32
11 22
12 51
13 23
14 2
15 24
16 1
17 64
18 27
19 51
20 20

About Pengpeng Zeng

Pengpeng Zeng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Geography, Planning and Development, having authored 32 papers that have together received 534 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (29 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Domain Adaptation and Few-Shot Learning (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (489 citations), Artificial Intelligence (265 citations) and Computational Mathematics (2 citations). Pengpeng Zeng has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Lianli Gao, Jingkuan Song, Heng Tao Shen, Xiangpeng Li, Haonan Zhang, Lei Yu, Meng Wang, Yuan-Fang Li, Shuaicheng Liu and Donghao Liu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

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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