Jiangpeng He

677 citations
34 papers · 303 · h-index 10

Impact in

Papers in

Jiangpeng He

26 papers receiving 289 citations

Peers

Jiangpeng He
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 93
  • Artificial Intelligence 129
  • Public Health, Environmental and Occupational Health 79
  • Media Technology 17
  • Biomedical Engineering 58
Replace Zeman Shao with:
Zeman Shao United States
Chun Pong Lau United States
Yuanzhi Liang China
Eugene T. Y. Chang United Kingdom
S. X. Li China
AKM Shahariar Azad Rabby Bangladesh
Ishan R. Dave India
Cholwich Nattee Thailand
Alexandra Stefan United States
Zhiwei Chen China
Jiangpeng He relative to Zeman Shao United States Zeman Shao's profile →
Citations per field
00.5×3.4×
Zeman Shao · 1×
Citations per year

Countries citing papers authored by Jiangpeng He

Since Specialization
Citations

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

Fields of papers citing papers by Jiangpeng He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202094
2 202135
3 202031
4 202418
5 202316
6 202116
7 202214
8 202212
9 202112
10 20239
11 20248
12 20236
13 20245
14 20225
15 20224
16 20233
17 20242
18 20232
19 20242
20 20242

About Jiangpeng He

Jiangpeng He is a scholar working on Public Health, Environmental and Occupational Health, Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 34 papers that have together received 303 indexed citations. Recurring topics across this work include Nutritional Studies and Diet (13 papers), Advanced Chemical Sensor Technologies (10 papers), Domain Adaptation and Few-Shot Learning (7 papers), Image Retrieval and Classification Techniques (4 papers), COVID-19 diagnosis using AI (3 papers), Multimodal Machine Learning Applications (3 papers), Culinary Culture and Tourism (2 papers) and Diet and metabolism studies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (93 citations), Artificial Intelligence (129 citations), Public Health, Environmental and Occupational Health (79 citations), Media Technology (17 citations) and Biomedical Engineering (58 citations). Jiangpeng He has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Fengqing Zhu, Zeman Shao, Carol J. Boushey, Janine Wright, Deborah A. Kerr, Heather A. Eicher‐Miller, Yue Han, Xinyue Pan, Jinge Ma and Justin Yang. Their work appears in journals such as Nutrients, IEEE Transactions on Multimedia, IEEE Journal of Biomedical and Health Informatics, Electronic Imaging and 2022 IEEE International Conference on Image Processing (ICIP).

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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