Chiun-Li Chin

408 total citations
39 papers, 267 citations indexed

About

Chiun-Li Chin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biomedical Engineering. According to data from OpenAlex, Chiun-Li Chin has authored 39 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 9 papers in Biomedical Engineering. Recurrent topics in Chiun-Li Chin's work include AI in cancer detection (6 papers), Brain Tumor Detection and Classification (5 papers) and Medical Imaging and Analysis (4 papers). Chiun-Li Chin is often cited by papers focused on AI in cancer detection (6 papers), Brain Tumor Detection and Classification (5 papers) and Medical Imaging and Analysis (4 papers). Chiun-Li Chin collaborates with scholars based in Taiwan, Japan and Australia. Chiun-Li Chin's co-authors include Tzu-Chieh Weng, Chin‐Teng Lin, Yu‐Liang Kuo, Ming‐Chi Wu, Yeu‐Sheng Tyan, Shing-Hong Liu, Chun-Hung Su, Wenxi Chen, Xin Zhu and Jingwen Wang and has published in prestigious journals such as Sensors, Nutrients and Heliyon.

In The Last Decade

Chiun-Li Chin

37 papers receiving 246 citations

Peers

Chiun-Li Chin
Comparison fields: 5 of 66
  • Neurology 76
  • Biomedical Engineering 73
  • Computer Vision and Pattern Recognition 70
  • Epidemiology 66
  • Radiology, Nuclear Medicine and Imaging 52
Replace Asit Kumar Subudhi with:
Asit Kumar Subudhi India
K. Meenakshi India
Yunendah Nur Fuadah Indonesia
Charturong Tantibundhit Thailand
Paweł Badura Poland
Tahia Tazin Bangladesh
Meghavi Rana India
Solon A. Peixoto Brazil
Chandradeep Bhatt India
Miguel Monteiro United Kingdom
Asit Kumar Subudhi India View profile →
Citations per field, relative to Chiun-Li Chin
Chiun-Li Chin · 1×
Citations per year, relative to Chiun-Li Chin
Chiun-Li Chin · 1×

Countries citing papers authored by Chiun-Li Chin

Since Specialization
Citations

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

Fields of papers citing papers by Chiun-Li Chin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chiun-Li Chin. 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 Chiun-Li Chin. The network helps show where Chiun-Li Chin may publish in the future.

Co-authorship network of co-authors of Chiun-Li Chin

This figure shows the co-authorship network connecting the top 25 collaborators of Chiun-Li Chin. A scholar is included among the top collaborators of Chiun-Li Chin 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 Chiun-Li Chin. Chiun-Li Chin 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
# Work Indexed citations
1 1
2 8
3 5
4 1
5 4
6 7
7 2
8 8
9 3
10 2
11 5
12
Hybrid-neuro-fuzzy system and Adaboost-classifier for classifying breast calcification
2
13 4
14
Fully Automatic Abdominal Fat Segmentation System from a Low Resolution CT Image
2
15 38
16 1
17
Personal Healthy Diet and Calorie Monitoring System using Fuzzy Inference in Smart Phones
2
18 1
19 0
20 9

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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