Xinjun Ma

593 citations
4 papers · 125 · h-index 4

Impact in

    • Advanced Vision and Imaging
    • Optical measurement and interference techniques
    • Advanced Image Processing Techniques
    • Image Enhancement Techniques
    • 3D Surveying and Cultural Heritage

Papers in

Journals
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)
Partner nations
ChinaFranceHong Kong

In The Last Decade

Xinjun Ma

4 papers receiving 116 citations

Peers

Xinjun Ma
Comparison fields: 5 of 28
  • Computer Vision and Pattern Recognition 103
  • Geology 24
  • Media Technology 21
  • Computer Graphics and Computer-Aided Design 5
  • Aerospace Engineering 18
Replace Ujwala Patil with:
Ujwala Patil India
Deqing Sun United States
Nianjin Ye China
Tuo Feng China
Mustafa Gökhan Uzunbaş United States
Devin Guillory United States
Russ Webb United States
Lang Nie China
Pierre Moulon France
Zhaoyang Lyu China
Xinjun Ma relative to Ujwala Patil India Ujwala Patil's profile →
Citations per field
00.5×1.6×
Ujwala Patil · 1×
Citations per year

Countries citing papers authored by Xinjun Ma

Since Specialization
Citations

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

Fields of papers citing papers by Xinjun Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Xinjun Ma, 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 Xinjun Ma Line = papers co-authored together Xinjun Ma links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown
#Work
1 202190
2 201921
3
A face detection algorithm based on modified skin-color model
20139
4 20115

About Xinjun Ma

Xinjun Ma is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Oncology, Epidemiology and Artificial Intelligence, having authored 4 papers that have together received 125 indexed citations. Recurring topics across this work include Cervical Cancer and HPV Research (1 paper), AI in cancer detection (1 paper), Face and Expression Recognition (1 paper), Remote Sensing and Land Use (1 paper), Face recognition and analysis (1 paper), Advanced Algorithms and Applications (1 paper), Image and Signal Denoising Methods (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (103 citations), Geology (24 citations), Media Technology (21 citations), Computer Graphics and Computer-Aided Design (5 citations) and Aerospace Engineering (18 citations). Xinjun Ma has collaborated with scholars based in China, France and Hong Kong. Frequent co-authors include Qirui Wang, Yue Gong, Jingwei Huang, Tingting Chen, Weiguo Lü, Xin Zhang, Jian Wu, Wenzhe Wang, Danny Z. Chen and Hongqiao Zhang. Their work appears in journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

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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