Weipeng Cao

3.2k citations
66 papers · 2.3k indexed · 1 hit paper · h-index 22

Impact in

Papers in

Weipeng Cao

58 papers receiving 2.3k citations

Hit Papers

A review on neural networks with random weights 2017 · 351 citations
3512017202620202023100200300

Peers

Weipeng Cao
Comparison fields: 5 of 164
  • Biomaterials 401
  • Artificial Intelligence 486
  • Biomedical Engineering 513
  • Molecular Biology 778
  • Computer Vision and Pattern Recognition 220
Replace Chunxi Liu with:
Chunxi Liu China
Yonghong Song China
Rui Cai China
Xinyang Zhang China
Weijie Su United States
Yi Shen China
Wenhan Wang China
Jing Gao China
Xiaohe Chen China
Yan Wang China
Weipeng Cao relative to Chunxi Liu China Chunxi Liu's profile →
Citations per field
00.5×1.5×
Chunxi Liu · 1×
Citations per year

Countries citing papers authored by Weipeng Cao

Since Specialization
Citations

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

Fields of papers citing papers by Weipeng Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 202314
4 202321
5 20237
6 20230
7 202210
8 202218
9 20227
10 202142
11 20211
12 201912
13 201623
14 201535
15 201412
16 201473
17 201464
18 201413
19 2012183
20 2010332

About Weipeng Cao

Weipeng Cao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Software, Media Technology and Information Systems, having authored 66 papers that have together received 2.3k indexed citations. Recurring topics across this work include Machine Learning and ELM (21 papers), Domain Adaptation and Few-Shot Learning (17 papers), Neural Networks and Applications (12 papers), Multimodal Machine Learning Applications (9 papers), Face and Expression Recognition (8 papers), RNA Interference and Gene Delivery (5 papers), Nanoplatforms for cancer theranostics (4 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Biomaterials (401 citations), Artificial Intelligence (486 citations), Biomedical Engineering (513 citations), Molecular Biology (778 citations) and Computer Vision and Pattern Recognition (220 citations). Weipeng Cao has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Xizhao Wang, Xing‐Jie Liang, Zhong Ming, Jinzhu Gao, Guozhang Zou, Xu Zhang, Ye‐Guang Chen, Chan Gao, Sha He and Yuran Huang. Their work appears in journals such as International Journal of Machine Learning and Cybernetics, Nanoscale, Neurocomputing, Engineering Applications of Artificial Intelligence and Soft Computing.

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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