Keke He

466 citations
19 papers · 257 · h-index 10

Impact in

    • Face recognition and analysis
    • Face and Expression Recognition
    • Advanced Neural Network Applications
    • Video Surveillance and Tracking Methods
    • Digital Imaging for Blood Diseases
    • Brain Tumor Detection and Classification

Papers in

Keke He

19 papers receiving 250 citations

Peers

Keke He
Comparison fields: 5 of 63
  • Computer Vision and Pattern Recognition 140
  • Neurology 25
  • Health Informatics 4
  • Artificial Intelligence 100
  • Radiology, Nuclear Medicine and Imaging 41
Replace Sanjoy Kumar Saha with:
Sanjoy Kumar Saha India
Zhezhou Yu China
Shir Li Wang Malaysia
Chandradeep Bhatt India
Mohamad Khir Abdullah Malaysia
Anam Mustaqeem Pakistan
Ferhat Bozkurt Türkiye
Harold Brayan Arteaga-Arteaga Colombia
Mario Alejandro Bravo-Ortíz Colombia
Keke He relative to Sanjoy Kumar Saha India Sanjoy Kumar Saha's profile →
Citations per field
00.5×3.7×
Sanjoy Kumar Saha · 1×
Citations per year

Countries citing papers authored by Keke He

Since Specialization
Citations

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

Fields of papers citing papers by Keke He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Keke He, 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 Keke He Line = papers co-authored together Keke He links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 201741
2 201736
3 201828
4 202322
5 202322
6 202220
7 202319
8 202415
9 202313
10 202313
11 20248
12 20246
13 20235
14 20152
15 20182
16 20242
17
Analysis of Influential Factors for Ore-rock Fragmentation Prediction
20111
18 20171
19 20111

About Keke He

Keke He is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Control and Systems Engineering and Signal Processing, having authored 19 papers that have together received 257 indexed citations. Recurring topics across this work include AI in cancer detection (4 papers), Digital Imaging for Blood Diseases (3 papers), Advanced Neural Network Applications (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Target Tracking and Data Fusion in Sensor Networks (3 papers), Face and Expression Recognition (2 papers), Face recognition and analysis (2 papers) and Medical Imaging and Analysis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (140 citations), Neurology (25 citations), Health Informatics (4 citations), Artificial Intelligence (100 citations) and Radiology, Nuclear Medicine and Imaging (41 citations). Keke He has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Fangfang Gou, Jia Wu, Xiangyang Xue, Yanwei Fu, Yu–Gang Jiang, Limiao Li, Rui Feng, Yuan Liu, Yulong Sun and Jianhui Jian. Their work appears in journals such as Wireless Communications and Mobile Computing, Heliyon, Applied Energy, Computers & Electrical Engineering and Journal of Intelligent & Fuzzy 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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