Qingfeng Wu

969 citations
52 papers · 506 · h-index 9

Impact in

Papers in

Qingfeng Wu

44 papers receiving 486 citations

Peers

Qingfeng Wu
Comparison fields: 5 of 100
  • Experimental and Cognitive Psychology 202
  • Human-Computer Interaction 73
  • Cognitive Neuroscience 230
  • Complementary and alternative medicine 52
  • Signal Processing 39
Replace Esmeralda C. Djamal with:
Esmeralda C. Djamal Indonesia
Xinchun Cui China
Jianliang Min China
P. Bhuvaneswari India
J. Satheesh Kumar India
Hamdi Dibeklioğlu Türkiye
Guanming Lu China
Abdullah Y. Muaad India
Mahmoud Shoman Egypt
Mohan Karnati India
Qingfeng Wu relative to Esmeralda C. Djamal Indonesia Esmeralda C. Djamal's profile →
Citations per field
00.5×10×13×
Esmeralda C. Djamal · 1×
Citations per year

Countries citing papers authored by Qingfeng Wu

Since Specialization
Citations

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

Fields of papers citing papers by Qingfeng Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018229
2
Feature extraction and automatic recognition of plant leaf using artificial neural network
200748
3 202143
4 202122
5 202314
6 202313
7 202311
8 201810
9 20209
10 20248
11 20238
12 20217
13 20136
14 20206
15 20235
16 20165
17 20114
18 20114
19 20164
20 20164

About Qingfeng Wu

Qingfeng Wu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Signal Processing, having authored 52 papers that have together received 506 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (5 papers), Anomaly Detection Techniques and Applications (5 papers), Traditional Chinese Medicine Studies (5 papers), EEG and Brain-Computer Interfaces (4 papers), Recommender Systems and Techniques (4 papers), Network Security and Intrusion Detection (4 papers), Face and Expression Recognition (3 papers) and Image Retrieval and Classification Techniques (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (202 citations), Human-Computer Interaction (73 citations), Cognitive Neuroscience (230 citations), Complementary and alternative medicine (52 citations) and Signal Processing (39 citations). Qingfeng Wu has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Yingdong Wang, Ming Qiu, Xiaowei Chen, Changle Zhou, Xiaojuan Hu, Jiatuo Xu, Xuxiang Ma, Jing-bin Huang, Liping Tu and Ji Cui. Their work appears in journals such as Sensors, Journal of Food Composition and Analysis, Scientific Reports, International Journal of Biological Macromolecules and Food Chemistry.

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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