Chunquan Liang

947 citations
8 papers · 666 indexed · 1 hit paper · h-index 4
Topics
Data Stream Mining Techniques (4 papers)Machine Learning and Data Classification (4 papers)Anomaly Detection Techniques and Applications (3 papers)

In The Last Decade

Chunquan Liang

7 papers receiving 614 citations

Hit Papers

Real-Time Detection of Apple Leaf Diseases Using Deep Lea...20192026202120232019200400600

Peers

Chunquan Liang
Comparison fields: 5 of 55
  • Plant Science 562
  • Analytical Chemistry 223
  • Ecology 93
  • Artificial Intelligence 66
  • Cell Biology 57
Replace Shanwen Zhang with:
Shanwen Zhang China
Yuxiang Li China
Edna C. Too Kenya
Mohammed Brahimi Algeria
G. Geetharamani India
J. Arun Pandian India
Aravind Krishnaswamy Rangarajan India
Shilpi Harnal India
Sulieman Bani‐Ahmad Jordan
Jinzhu Lu China
Chunquan Liang relative to Shanwen Zhang China Shanwen Zhang's profile →
Citations per field
00.5×1.7×
Shanwen Zhang · 1×
Citations per year

Countries citing papers authored by Chunquan Liang

Since Specialization
Citations

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

Fields of papers citing papers by Chunquan Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunquan Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Chunquan Liang. A scholar is included among the top collaborators of Chunquan Liang 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 Chunquan Liang. Chunquan Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 0
2 1
3
Real-Time Detection of Apple Leaf Diseases Using Deep Learning Approach Based on Improved Convolutional Neural Networksbreakdown →
602
4 2
5 2
6 6
7 27
8
Decision Tree for Dynamic and Uncertain Data Streams
26

About Chunquan Liang

Chunquan Liang is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications, having authored 8 papers that have together received 666 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (4 papers), Machine Learning and Data Classification (4 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Analytical Chemistry (223 citations), Plant Science (562 citations) and Ecology (93 citations). Chunquan Liang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Bin Liu, Dongjian He, Peng Jiang, Yuehan Chen, Shuicheng Yan, Qunliang Song, Peng Shi, Zhengguo Hu, Zhengguo Hu and Yang Zhang. Their work appears in journals such as IEEE Access, Information Sciences 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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