Chun‐Chieh Yang

66 papers receiving 1.0k citations

Peers

Chun‐Chieh Yang
Comparison fields: 5 of 111
  • Analytical Chemistry 427
  • Biophysics 69
  • Environmental Engineering 150
  • Animal Science and Zoology 92
  • Plant Science 312
Replace Samsuzana Abd Aziz with:
Samsuzana Abd Aziz Malaysia
Hui Fang China
Knut Kvaal Norway
Jinglu Tan United States
Marie-France Destain Belgium
Xin Sun United States
Qian Sun China
Yao Zhang China
G.W.A.M. van der Heijden Netherlands
Chun‐Chieh Yang relative to Samsuzana Abd Aziz Malaysia Samsuzana Abd Aziz's profile →
Citations per field
00.5×1.5×2.2×
Samsuzana Abd Aziz · 1×
Citations per year

Countries citing papers authored by Chun‐Chieh Yang

Since Specialization
Citations

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

Fields of papers citing papers by Chun‐Chieh Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003107
2
Application of artificial neural networks in image recognition and classification of crop and weeds
200085
3 200761
4 201757
5 200357
6 199755
7
Recognition of weeds with image processing and their use with fuzzy logic for precision farming
200044
8 200442
9 200339
10 200939
11 200338
12 201138
13 199732
14 200830
15 200628
16 201425
17 200523
18 200622
19 200721
20 200717

About Chun‐Chieh Yang

Chun‐Chieh Yang is a scholar working on Analytical Chemistry, Hardware and Architecture, Molecular Biology, Plant Science and Computer Networks and Communications, having authored 68 papers that have together received 1.1k indexed citations. Recurring topics across this work include Spectroscopy and Chemometric Analyses (30 papers), Parallel Computing and Optimization Techniques (11 papers), Listeria monocytogenes in Food Safety (8 papers), Identification and Quantification in Food (7 papers), Hydrological Forecasting Using AI (6 papers), Hydrology and Watershed Management Studies (6 papers), Smart Agriculture and AI (6 papers) and Meat and Animal Product Quality (5 papers). The work is most often cited by research in Analytical Chemistry (427 citations), Biophysics (69 citations), Environmental Engineering (150 citations), Animal Science and Zoology (92 citations) and Plant Science (312 citations). Chun‐Chieh Yang has collaborated with scholars based in United States, Taiwan and Canada. Frequent co-authors include Shiv O. Prasher, Kuanglin Chao, Moon S. Kim, Yud-Ren Chen, Diane E. Chan, R. Lacroix, Hosahalli S. Ramaswamy, Alan M. Lefcourt, Byoung–Kwan Cho and Pradeep Goel. Their work appears in journals such as Canadian Water Resources Journal / Revue canadienne des ressources hydriques, Biosystems Engineering, Journal of Food Engineering, Journal of Systems Architecture and Agricultural Systems.

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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