Cong Lin

58 papers receiving 1.3k citations

Peers

Cong Lin
Comparison fields: 5 of 121
  • Media Technology 422
  • Software 182
  • Safety, Risk, Reliability and Quality 360
  • Statistics, Probability and Uncertainty 194
  • Atmospheric Science 275
Replace D. Chaudhuri with:
D. Chaudhuri India
Arun R. Kumar India
Elisabetta Binaghi Italy
Shihai Wang China
Xin James He China
I. Kanellopoulos Italy
Mingming Xu China
Cong Lin relative to D. Chaudhuri India D. Chaudhuri's profile →
Citations per field
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D. Chaudhuri · 1×
Citations per year

Countries citing papers authored by Cong Lin

Since Specialization
Citations

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

Fields of papers citing papers by Cong Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017262
2 202089
3 202074
4 202067
5 202164
6 202055
7 201743
8 202043
9 201640
10 201738
11 201438
12 202132
13 202332
14 201928
15 202026
16 202021
17 202018
18 202018
19 202318
20 201918

About Cong Lin

Cong Lin is a scholar working on Media Technology, Safety, Risk, Reliability and Quality, Software, Statistics, Probability and Uncertainty and Atmospheric Science, having authored 66 papers that have together received 1.3k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (16 papers), Reliability and Maintenance Optimization (15 papers), Remote Sensing and Land Use (13 papers), Remote Sensing in Agriculture (12 papers), Software Reliability and Analysis Research (8 papers), Statistical Distribution Estimation and Applications (6 papers), Land Use and Ecosystem Services (5 papers) and Risk and Safety Analysis (5 papers). The work is most often cited by research in Media Technology (422 citations), Software (182 citations), Safety, Risk, Reliability and Quality (360 citations), Statistics, Probability and Uncertainty (194 citations) and Atmospheric Science (275 citations). Cong Lin has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Peijun Du, Erzhu Li, Alim Samat, Junshi Xia, Lirong Cui, Xin Wang, Sicong Liu, Qingan Qiu, Jingjing Wang and Shanchuan Guo. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, Reliability Engineering & System Safety, Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability and IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

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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