Qingchun Feng

1.4k citations
66 papers · 1.0k indexed · 1 hit paper · h-index 20
Topics
Smart Agriculture and AI (40 papers)Spectroscopy and Chemometric Analyses (8 papers)Plant Virus Research Studies (8 papers)
Journals
SHILAP Revista de lepidopterologíaRemote SensingComputers and Electronics in Agriculture
Partner nations
ChinaUnited States

In The Last Decade

Qingchun Feng

61 papers receiving 991 citations

Hit Papers

Dynamic Task Planning for Multi-Arm Harvesting Robots Und...2025202620255101520

Peers

Qingchun Feng
Comparison fields: 5 of 90
  • Plant Science 740
  • Mechanical Engineering 218
  • Biomedical Engineering 124
  • Computer Vision and Pattern Recognition 111
  • Control and Systems Engineering 92
Replace C.W. Bac with:
C.W. Bac Netherlands
Ya Xiong Norway
R. Barth Netherlands
Lars Grimstad Norway
B.A.J. van Tuijl Netherlands
Chris Lehnert Australia
Luis Emmi Spain
Jianneng Chen China
Mike Duke New Zealand
Long He United States
Qingchun Feng relative to C.W. Bac Netherlands C.W. Bac's profile →
Citations per field
00.5×5.0×
C.W. Bac · 1×
Citations per year

Countries citing papers authored by Qingchun Feng

Since Specialization
Citations

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

Fields of papers citing papers by Qingchun Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingchun Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Qingchun Feng. A scholar is included among the top collaborators of Qingchun Feng 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 Qingchun Feng. Qingchun Feng 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
#WorkIndexed citations
1 2
2 1
3 20
4 0
5 2
6 2
7 7
8 5
9 4
10 1
11 1
12 26
13 6
14 2
15 6
16
Tomato seed varieties recognition based on principal component analysis and LVQ neural network
1
17
Melon seed variety identification based on hyperspectral technology combined with discriminant analysis.
1
18 27
19 16
20 69

About Qingchun Feng

Qingchun Feng is a scholar working on Plant Science, Analytical Chemistry and Control and Systems Engineering, having authored 66 papers that have together received 1.0k indexed citations. Recurring topics across this work include Smart Agriculture and AI (40 papers), Spectroscopy and Chemometric Analyses (8 papers) and Plant Virus Research Studies (8 papers). The work is most often cited by research in Plant Science (740 citations), Analytical Chemistry (81 citations) and Mechanical Engineering (218 citations). Qingchun Feng has collaborated with scholars based in China and United States. Frequent co-authors include Tao Li, Feng Xie, Xiu Wang, Quan Qiu, Kai Jiang, Wei Zou, Chunjiang Zhao, Yajun Li, Chunfeng Zhang and Wengang Zheng. Their work appears in journals such as SHILAP Revista de lepidopterología, Remote Sensing and Computers and Electronics in Agriculture.

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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