Can Yang

29 papers receiving 497 citations

Can Yang's Hit Papers

Machine learning-based landslide susceptibility assessment with optimized ratio of landslide to non-landslide samples 2022 · 126 citations
1260+1+2Years since publication4080120

Peers

Can Yang
Comparison fields: 5 of 106
  • Management, Monitoring, Policy and Law 207
  • Safety, Risk, Reliability and Quality 75
  • General Energy 8
  • Global and Planetary Change 114
  • Economics and Econometrics 108
Replace Mutasem Sh. Alkhasawneh with:
Mutasem Sh. Alkhasawneh Jordan
Nitin Anand Shrivastava India
Shanti Majithia United Kingdom
Rong He United States
Lea Tien Tay Malaysia
Alihan Teke Türkiye
Ida Marie Solbrekke Norway
Can Yang relative to Mutasem Sh. Alkhasawneh Jordan Mutasem Sh. Alkhasawneh's profile →
Citations per field
00.5×10×15×21.6×
Mutasem Sh. Alkhasawneh · 1×
Citations per year

Countries citing papers authored by Can Yang

Since Specialization
Citations

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

Fields of papers citing papers by Can Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine learning-based landslide susceptibility assessment with optimized ratio of landslide to non-landslide samples
Hit paper breakdown →
2022126
2 2018114
3 202246
4 202237
5 202127
6 202126
7 201925
8 202111
9 202410
10 201810
11 20199
12 20149
13 20169
14 20245
15 20245
16 20205
17 20254
18 20253
19
Teaching Robotics with Robot Operating System (ROS) : A Behavior Model Perspective
20183
20 20243

About Can Yang

Can Yang is a scholar working on Safety, Risk, Reliability and Quality, Computer Vision and Pattern Recognition, Artificial Intelligence, Management, Monitoring, Policy and Law and Molecular Biology, having authored 30 papers that have together received 504 indexed citations. Recurring topics across this work include Landslides and related hazards (7 papers), Geotechnical Engineering and Analysis (7 papers), Video Surveillance and Tracking Methods (4 papers), Anomaly Detection Techniques and Applications (3 papers), Human Pose and Action Recognition (2 papers), Dam Engineering and Safety (2 papers), Plant Toxicity and Pharmacological Properties (2 papers) and Gastrointestinal Bleeding Diagnosis and Treatment (2 papers). The work is most often cited by research in Management, Monitoring, Policy and Law (207 citations), Safety, Risk, Reliability and Quality (75 citations), General Energy (8 citations), Global and Planetary Change (114 citations) and Economics and Econometrics (108 citations). Can Yang has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Leilei Liu, Xiaomi Wang, Faming Huang, Yue‐Jun Zhang, Fenghua Wen, Lei Huang, Yili Zhang, Shir Li Wang, Ting Xiao and Baopu Li. Their work appears in journals such as Bulletin of Engineering Geology and the Environment, Organic & Biomolecular Chemistry, Scientific Reports, Geoscience Frontiers and Process Safety and Environmental Protection.

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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