Qi Ming

1.6k total citations · 1 hit paper
29 papers, 768 citations indexed

About

Qi Ming is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Aerospace Engineering. According to data from OpenAlex, Qi Ming has authored 29 papers receiving a total of 768 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 10 papers in Media Technology and 9 papers in Aerospace Engineering. Recurrent topics in Qi Ming's work include Advanced Neural Network Applications (12 papers), Remote-Sensing Image Classification (10 papers) and Advanced Image and Video Retrieval Techniques (10 papers). Qi Ming is often cited by papers focused on Advanced Neural Network Applications (12 papers), Remote-Sensing Image Classification (10 papers) and Advanced Image and Video Retrieval Techniques (10 papers). Qi Ming collaborates with scholars based in China, Belgium and Singapore. Qi Ming's co-authors include Lingjuan Miao, Zhiqiang Zhou, Yunpeng Dong, Linhao Li, Hongwei Zhang, Xue Yang, Aleksandra Pižurica, Hongbo Li, Monika Wolf and Shujuan Wang and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Qi Ming

24 papers receiving 746 citations

Hit Papers

Dynamic Anchor Learning for Arbitrary-Oriented Object Det... 2021 2026 2022 2024 2021 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Dynamic Anchor Learning for Arbitrary-Oriented Object Detection
    2021 250 citations Qi Ming, Zhiqiang Zhou et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Qi Ming China 10 596 328 237 77 43 29 768
Fukun Bi China 14 401 0.7× 255 0.8× 269 1.1× 58 0.8× 91 2.1× 74 711
Yin Zhuang China 15 412 0.7× 417 1.3× 175 0.7× 92 1.2× 80 1.9× 64 754
Jihao Li China 10 378 0.6× 241 0.7× 124 0.5× 116 1.5× 52 1.2× 33 618
Jirui Yang China 6 986 1.7× 491 1.5× 405 1.7× 81 1.1× 71 1.7× 10 1.2k
Linbo Luo China 12 533 0.9× 480 1.5× 299 1.3× 22 0.3× 40 0.9× 39 774
Kun Fu China 11 308 0.5× 216 0.7× 156 0.7× 61 0.8× 50 1.2× 30 509
Haixia Bi China 11 217 0.4× 201 0.6× 196 0.8× 79 1.0× 61 1.4× 27 510
Liping Hou China 5 581 1.0× 258 0.8× 291 1.2× 63 0.8× 43 1.0× 11 748
Jiaqing Zhang China 8 159 0.3× 184 0.6× 243 1.0× 44 0.6× 52 1.2× 28 478

Countries citing papers authored by Qi Ming

Since Specialization
Citations

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

Fields of papers citing papers by Qi Ming

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qi Ming

This figure shows the co-authorship network connecting the top 25 collaborators of Qi Ming. A scholar is included among the top collaborators of Qi Ming 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 Qi Ming. Qi Ming 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
1.
Miao, Lingjuan, et al.. (2025). Unified Five-Distance Bounding Box Representation for Remote Sensing Oriented Object Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–17.
2.
Zhao, Xudong, et al.. (2025). Chirplet Fourier Analysis Network for Cross-Scene Classification of Multisource Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14.
3.
Ming, Qi, et al.. (2024). Gradient Calibration Loss for Fast and Accurate Oriented Bounding Box Regression. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 15 indexed citations
4.
Ming, Qi, et al.. (2024). Not All Boxes Are Equal: Learning to Optimize Bounding Boxes With Discriminative Distributions in Optical Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 12 indexed citations
5.
Ming, Qi, et al.. (2024). The Effect of Spanwise Folding on the Aerodynamic Performance of a Passively Deformed Flapping Wing. Biomimetics. 9(1). 42–42. 2 indexed citations
6.
Miao, Lingjuan, et al.. (2023). A Novel Object Detector Based on High-Quality Rotation Proposal Generation and Adaptive Angle Optimization. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–15. 8 indexed citations
7.
Ming, Qi, et al.. (2023). Task interleaving and orientation estimation for high-precision oriented object detection in aerial images. ISPRS Journal of Photogrammetry and Remote Sensing. 196. 241–255. 60 indexed citations
8.
Miao, Lingjuan, et al.. (2023). Optimized Point Set Representation for Oriented Object Detection in Remote-Sensing Images. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 4 indexed citations
9.
Ming, Qi, et al.. (2023). Towards Accurate Medical Image Segmentation With Gradient-Optimized Dice Loss. IEEE Signal Processing Letters. 31. 191–195. 18 indexed citations
10.
Miao, Lingjuan, et al.. (2022). Fine-Grained Object Detection in Remote Sensing Images via Adaptive Label Assignment and Refined-Balanced Feature Pyramid Network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 16. 71–82. 15 indexed citations
11.
Zhang, Yan, et al.. (2022). Research on Single Object Detection Technology Based on Infrared Multi-spectrum Fusion. 5. 1305–1310. 1 indexed citations
12.
Ming, Qi, Lingjuan Miao, Zhiqiang Zhou, Xue Yang, & Yunpeng Dong. (2021). Optimization for Arbitrary-Oriented Object Detection via Representation Invariance Loss. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 84 indexed citations
13.
Ming, Qi, Lingjuan Miao, Zhiqiang Zhou, & Yunpeng Dong. (2021). CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote-Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–14. 177 indexed citations
14.
Ming, Qi, et al.. (2021). Sparse Label Assignment for Oriented Object Detection in Aerial Images. Remote Sensing. 13(14). 2664–2664. 64 indexed citations
15.
Yang, Chunling, et al.. (2019). The Design of a Low Distortion Power Amplifier Based on Cascode. 1–4. 2 indexed citations
16.
Li, Hongbo, et al.. (2012). A REAL-TIME REGISTRATION METHOD OF AUGMENTED REALITY BASED ON SURF AND OPTICAL FLOW. 8 indexed citations
17.
Ming, Qi. (2012). The Analysis of Chinese Food Safety Issues: Legislations and Governmental Supervision. Chinese Law & Government. 45(1). 3–9. 6 indexed citations
18.
Ming, Qi. (2010). Binary Pattern of Right of Control of Companies during Integration Period——Also on the Demerit and Improvement in Our Bankruptcy Management System.
19.
Ming, Qi, et al.. (2009). Research on life prediction based on wavelet transform and ARMA model for space relay. 1275–1280. 6 indexed citations
20.

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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