Jing Peng

1.1k citations
22 papers · 628 · h-index 10

Impact in

Papers in

Jing Peng

19 papers receiving 617 citations

Peers

Jing Peng
Comparison fields: 5 of 91
  • Ecology, Evolution, Behavior and Systematics 264
  • Cellular and Molecular Neuroscience 227
  • Insect Science 137
  • Genetics 264
  • Immunology 121
Replace Hao Guo with:
Hao Guo China
Benjamin P. Smith United States
Yukiteru Ono Japan
Ulrich Stern United States
Zheng Zeng China
Kusum Singh India
Christopher Patrick Canada
Pooja Gupta India
Hongyi Nie China
Jing Peng relative to Hao Guo China Hao Guo's profile →
Citations per field
00.5×2.6×
Hao Guo · 1×
Citations per year

Countries citing papers authored by Jing Peng

Since Specialization
Citations

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

Fields of papers citing papers by Jing Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005247
2 2005193
3 202232
4 200527
5 201622
6 200121
7 200319
8 202316
9 202413
10 202211
11 20029
12 20237
13 20252
14
An Efficient Algorithm of Thinning Scanned Pencil Drawings
20002
15 20102
16 20022
17 20131
18 20111
19 20141
20 20230

About Jing Peng

Jing Peng is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Physiology, having authored 22 papers that have together received 628 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Face and Expression Recognition (3 papers), Image Retrieval and Classification Techniques (3 papers), Lattice Boltzmann Simulation Studies (2 papers), Extracellular vesicles in disease (2 papers), Blood properties and coagulation (2 papers), Neurobiology and Insect Physiology Research (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (264 citations), Cellular and Molecular Neuroscience (227 citations), Insect Science (137 citations), Genetics (264 citations) and Immunology (121 citations). Jing Peng has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Eric Kubli, Peder Zipperlen, Shanjun Chen, Thomas G. Honegger, Douglas R. Heisterkamp, Honghua Dai, Hyeran Byun, Byoung Chul Ko, Yves Choffat and Satoshi Ii. Their work appears in journals such as Physics of Fluids, Current Biology, Combinatorial Chemistry & High Throughput Screening, Frontiers in Endocrinology and Molecular Immunology.

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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