Qichuan Geng

12 papers receiving 772 citations

Hit Papers

The ApolloScape Open Dataset for Autonomous Driving and I...20192026202120232019100200300

Peers

Qichuan Geng
Comparison fields: 5 of 76
  • Computer Vision and Pattern Recognition 530
  • Automotive Engineering 255
  • Aerospace Engineering 157
  • Artificial Intelligence 144
  • Environmental Engineering 81
Replace Yuning Chai with:
Yuning Chai United States
Senthil Yogamani France
Raoul de Charette France
Claudius Gläser Germany
Xinjing Cheng China
Eduardo Arnold United Kingdom
Heinz Hertlein United Kingdom
Sławomir Bąk United States
Zhiyu Xiang China
Qichuan Geng relative to Yuning Chai United States Yuning Chai's profile →
Citations per field
00.5×3.8×
Yuning Chai · 1×
Citations per year

Countries citing papers authored by Qichuan Geng

Since Specialization
Citations

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

Fields of papers citing papers by Qichuan Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qichuan Geng

This figure shows the co-authorship network connecting the top 25 collaborators of Qichuan Geng. A scholar is included among the top collaborators of Qichuan Geng 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 Qichuan Geng. Qichuan Geng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 1
5 34
6 1
7 6
8 4
9 59
10 132
11
The ApolloScape Open Dataset for Autonomous Driving and Its Applicationbreakdown →
383
12 112
13 64
14 4
15 7

About Qichuan Geng

Qichuan Geng is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Software, having authored 15 papers that have together received 807 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Video Surveillance and Tracking Methods (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (530 citations), Automotive Engineering (255 citations) and Computer Graphics and Computer-Aided Design (27 citations). Qichuan Geng has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ruigang Yang, Xinyu Huang, Xinjing Cheng, Dingfu Zhou, Peng Wang, Zhong Zhou, Xiaochun Cao, Yuanqing Lin, Binbin Cao and Yixuan Li. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Intelligent Transportation Systems.

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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