Daoyu Lin

788 citations
26 papers · 500 · h-index 12

Impact in

    • Remote-Sensing Image Classification
    • Advanced Image Fusion Techniques
    • Advanced Image and Video Retrieval Techniques
    • Advanced Image Processing Techniques
    • Image and Signal Denoising Methods
    • Advanced Vision and Imaging

Papers in

Daoyu Lin

24 papers receiving 490 citations

Peers

Daoyu Lin
Comparison fields: 5 of 74
  • Media Technology 277
  • Computer Vision and Pattern Recognition 296
  • Atmospheric Science 89
  • Artificial Intelligence 104
  • Health Informatics 4
Replace Shaoteng Liu with:
Shaoteng Liu China
Erlei Zhang China
Xiuwen Gong Australia
Claude Cariou France
Dongdong Guan China
Claas Grohnfeldt Germany
Honghui Xu China
Yuhao Liu China
Fenlong Jiang China
Weiping Ni China
Daoyu Lin relative to Shaoteng Liu China Shaoteng Liu's profile →
Citations per field
00.5×1.6×
Shaoteng Liu · 1×
Citations per year

Countries citing papers authored by Daoyu Lin

Since Specialization
Citations

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

Fields of papers citing papers by Daoyu Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017172
2 202081
3 201843
4 201819
5 202219
6 201919
7 201818
8 202017
9
Weed recognition using Image Processing technique based on Leaf Parameters
201217
10 202416
11 202013
12 201913
13 20217
14 20217
15 20186
16 20176
17
Deep Unsupervised Representation Learning for Remote Sensing Images.
20165
18 20195
19 20244
20 20194

About Daoyu Lin

Daoyu Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Statistical and Nonlinear Physics and Ecology, having authored 26 papers that have together received 500 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Data Visualization and Analytics (5 papers), Advanced Image Processing Techniques (5 papers), Natural Language Processing Techniques (4 papers), Advanced Vision and Imaging (4 papers), Remote-Sensing Image Classification (4 papers), Topic Modeling (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Media Technology (277 citations), Computer Vision and Pattern Recognition (296 citations), Atmospheric Science (89 citations), Artificial Intelligence (104 citations) and Health Informatics (4 citations). Daoyu Lin has collaborated with scholars based in China and United States. Frequent co-authors include Guangluan Xu, Yang Wang, Xian Sun, Kun Fu, Wenjia Xu, Yunyan Zhang, Chibiao Ding, Jun Li, Yirong Wu and Xiaoyi Tang. Their work appears in journals such as Applied Sciences, IEEE Access, Remote Sensing, Linguistics Vanguard and Neurocomputing.

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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