Dan Shi

434 citations
17 papers · 329 · h-index 8

Impact in

Papers in

Dan Shi

16 papers receiving 327 citations

Peers

Dan Shi
Comparison fields: 5 of 69
  • Analytical Chemistry 102
  • Computer Vision and Pattern Recognition 134
  • Toxicology 15
  • Urban Studies 24
  • Spectroscopy 61
Replace Yuan Sun with:
Yuan Sun China
Huijuan Zhang China
Mahdi Vasighi Iran
Liu Shao United States
Guoquan Wang China
Haiyan Chen China
Ying Dou China
Zhaoxian Zhou United States
Xiuqiong Zhang China
Dan Shi relative to Yuan Sun China Yuan Sun's profile →
Citations per field
00.5×
Yuan Sun · 1×
Citations per year

Countries citing papers authored by Dan Shi

Since Specialization
Citations

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

Fields of papers citing papers by Dan Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 200662
2 201953
3 200649
4 202347
5 202129
6 202125
7 201824
8 202010
9 20236
10 20136
11 20235
12 20134
13 20154
14 20192
15
Multi-sensor image fusion algorithm considering neighborhood consistency in the nonsubsampled contourlet transform domain
20102
16 20111
17 20180

About Dan Shi

Dan Shi is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Urban Studies, Artificial Intelligence and Aerospace Engineering, having authored 17 papers that have together received 329 indexed citations. Recurring topics across this work include Face and Expression Recognition (7 papers), Advanced Image and Video Retrieval Techniques (7 papers), Remote-Sensing Image Classification (4 papers), Image Retrieval and Classification Techniques (4 papers), Advanced Computing and Algorithms (3 papers), Infrared Target Detection Methodologies (2 papers), Analytical chemistry methods development (2 papers) and Analytical Chemistry and Chromatography (2 papers). The work is most often cited by research in Analytical Chemistry (102 citations), Computer Vision and Pattern Recognition (134 citations), Toxicology (15 citations), Urban Studies (24 citations) and Spectroscopy (61 citations). Dan Shi has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Jingjing Li, Lei Zhu, Zhiyong Cheng, Zheng Zhang, Yun Shi, Jianghua Zhang, Kang Dai, Bin Lü, Ming Jiang and Surong Mei. Their work appears in journals such as Biomedical Chromatography, Journal of Visual Communication and Image Representation, ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Neural Networks and Learning Systems and Journal of Pharmaceutical and Biomedical Analysis.

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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