Hongquan Qu

756 citations
75 papers · 558 indexed · h-index 13
Topics
Advanced Neural Network Applications (16 papers)Advanced Fiber Optic Sensors (13 papers)EEG and Brain-Computer Interfaces (8 papers)
Journals
SHILAP Revista de lepidopterologíaApplied EnergyAtmospheric Environment
Partner nations
ChinaUnited StatesNorway

In The Last Decade

Hongquan Qu

72 papers receiving 534 citations

Peers

Hongquan Qu
Comparison fields: 5 of 81
  • Electrical and Electronic Engineering 142
  • Artificial Intelligence 131
  • Control and Systems Engineering 116
  • Computer Vision and Pattern Recognition 92
  • Cognitive Neuroscience 77
Replace H. Selçuk Noğay with:
H. Selçuk Noğay Türkiye
Wei Fan China
Fusheng Zha China
Pengcheng Liu China
Alberto Rodríguez Spain
Tangfei Tao China
Shuanfeng Zhao China
Jiahong Li China
Bo Yin China
Hongquan Qu relative to H. Selçuk Noğay Türkiye H. Selçuk Noğay's profile →
Citations per field
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H. Selçuk Noğay · 1×
Citations per year

Countries citing papers authored by Hongquan Qu

Since Specialization
Citations

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

Fields of papers citing papers by Hongquan Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongquan Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Hongquan Qu. A scholar is included among the top collaborators of Hongquan Qu 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 Hongquan Qu. Hongquan Qu 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 8
4 1
5 2
6 3
7 7
8 15
9 11
10 1
11 12
12 8
13 3
14 11
15 20
16 5
17 11
18 1
19 15
20 3

About Hongquan Qu

Hongquan Qu is a scholar working on Computer Vision and Pattern Recognition, Environmental Engineering and Artificial Intelligence, having authored 75 papers that have together received 558 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (16 papers), Advanced Fiber Optic Sensors (13 papers) and EEG and Brain-Computer Interfaces (8 papers). The work is most often cited by research in Control and Systems Engineering (116 citations), Computer Vision and Pattern Recognition (92 citations) and Artificial Intelligence (131 citations). Hongquan Qu has collaborated with scholars based in China, United States and Norway. Frequent co-authors include Liping Pang, Tong Zheng, Changan Liu, Yanping Wang, Shaohong Li, Yuan Zhang, Xiaoru Wanyan, Peixin Gao, Jingyu Zhai and Tao Yu. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Energy and Atmospheric Environment.

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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