Pengfei Chen

2.5k citations
18 papers · 1.6k indexed · 1 hit paper · h-index 10

Pengfei Chen

18 papers receiving 1.6k citations

Hit Papers

Understanding Convolution for Semantic Segmentation1.4k20182026202020234008001.2k

Peers

Pengfei Chen
Comparison fields: 5 of 125
  • Computer Vision and Pattern Recognition 994
  • Media Technology 302
  • Artificial Intelligence 340
  • Industrial and Manufacturing Engineering 102
  • Ocean Engineering 106
Replace Panqu Wang with:
Panqu Wang United States
Zehua Huang China
Tian-Xing Xu China
Ralph R. Martin United Kingdom
Jingbo Wang China
Xuran Pan China
Kuiyuan Yang China
Quan Zhou China
Zheng-Ning Liu China
Pengfei Chen relative to Panqu Wang United States Panqu Wang's profile →
Citations per field
00.5×1.5×2.3×
Panqu Wang · 1×
Citations per year

Countries citing papers authored by Pengfei Chen

Since Specialization
Citations

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

Fields of papers citing papers by Pengfei Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

18 of 18 papers shown
#Work
1 20244
2 20242
3 20243
4 202414
5 202313
6 202341
7 20235
8 202311
9 202225
10 202075
11 20203
12 201927
13
Understanding Convolution for Semantic Segmentationbreakdown →
20181366
14 201827
15 20173
16 201610
17 20153
18 20085

About Pengfei Chen

Pengfei Chen is a scholar working on Transportation, Computer Vision and Pattern Recognition and Media Technology, having authored 18 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Urban Transport and Accessibility (3 papers), Image Enhancement Techniques (2 papers), Optical measurement and interference techniques (2 papers), Robotics and Sensor-Based Localization (2 papers), Human Mobility and Location-Based Analysis (1 paper) and Migration, Aging, and Tourism Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (994 citations), Media Technology (302 citations) and Artificial Intelligence (340 citations). Pengfei Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Garrison W. Cottrell, Zehua Huang, Ding Liu, Ye Yuan, Xiaodi Hou, Panqu Wang, Yuan Wang, Jingmin Xu, Ping Wang and Meng Ma. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.

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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