Jianchao Tan

27 papers receiving 544 citations

Peers

Jianchao Tan
Comparison fields: 5 of 62
  • Computer Vision and Pattern Recognition 441
  • Artificial Intelligence 132
  • Computer Graphics and Computer-Aided Design 100
  • Atomic and Molecular Physics, and Optics 56
  • Computational Mechanics 44
Replace Chengying Gao with:
Chengying Gao China
Elisa Drelie Gelasca Switzerland
Takuya Funatomi Japan
Luís Paulo Santos Portugal
Paul Upchurch United States
Wenju Xu United States
Zhengyou Zhang United States
Chong Mou China
Thomas Leimkühler Germany
Yael Moses Israel
Jianchao Tan relative to Chengying Gao China Chengying Gao's profile →
Citations per field
00.5×6.5×
Chengying Gao · 1×
Citations per year

Countries citing papers authored by Jianchao Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jianchao Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianchao Tan

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 8
3 7
4 2
5 7
6 4
7 10
8 9
9 9
10 0
11
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework
9
12 73
13
UMEC: Unified model and embedding compression for efficient recommendation systems
2
14 113
15 14
16 2
17 19
18 64
19 29
20 6

About Jianchao Tan

Jianchao Tan is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 28 papers that have together received 550 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (11 papers), Computer Graphics and Visualization Techniques (8 papers) and Image Enhancement Techniques (8 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (100 citations), Computer Vision and Pattern Recognition (441 citations) and Human-Computer Interaction (29 citations). Jianchao Tan has collaborated with scholars based in United States, China and Finland. Frequent co-authors include Yotam Gingold, Jyh‐Ming Lien, Jose Echevarria, Xiaohan Ding, Guiguang Ding, Yuchen Guo, Jungong Han, Hong Mo, Wenqi Ren and Lei Wang. Their work appears in journals such as ACM Transactions on Graphics, Neurocomputing 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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