Yi Ma

1.1k total citations · 1 hit paper
27 papers, 728 citations indexed

About

Yi Ma is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Electrical and Electronic Engineering. According to data from OpenAlex, Yi Ma has authored 27 papers receiving a total of 728 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 8 papers in Media Technology and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Yi Ma's work include Advanced Image Processing Techniques (5 papers), Advanced Image Fusion Techniques (4 papers) and Image and Signal Denoising Methods (4 papers). Yi Ma is often cited by papers focused on Advanced Image Processing Techniques (5 papers), Advanced Image Fusion Techniques (4 papers) and Image and Signal Denoising Methods (4 papers). Yi Ma collaborates with scholars based in China, United States and Sweden. Yi Ma's co-authors include Cong Yao, Xiang Bai, Wenyu Liu, Zhuowen Tu, Peiqi Duan, Boxin Shi, Jiajie Peng, Zhaopeng Meng, Jianye Hao and Jiawen Lu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, BMC Bioinformatics and Electronics.

In The Last Decade

Yi Ma

23 papers receiving 700 citations

Hit Papers

Detecting texts of arbitrary orientations in natural images 2012 2026 2016 2021 2012 100 200 300 400 500
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. Detecting texts of arbitrary orientations in natural images
    2012 505 citations Cong Yao, Xiang Bai 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
Yi Ma China 7 561 300 82 41 36 27 728
Shanmuganathan Raman India 16 519 0.9× 200 0.7× 209 2.5× 33 0.8× 17 0.5× 95 854
Satoshi Naoi Japan 13 516 0.9× 165 0.6× 164 2.0× 21 0.5× 10 0.3× 81 649
Siwei Feng United States 11 700 1.2× 171 0.6× 289 3.5× 33 0.8× 30 0.8× 27 927
Haishun Du China 11 262 0.5× 69 0.2× 162 2.0× 26 0.6× 26 0.7× 38 501
Ziqi Zhu China 9 370 0.7× 60 0.2× 69 0.8× 60 1.5× 10 0.3× 18 497
Huihuang Zhao China 10 210 0.4× 53 0.2× 70 0.9× 20 0.5× 33 0.9× 52 392

Countries citing papers authored by Yi Ma

Since Specialization
Citations

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

Fields of papers citing papers by Yi Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yi Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Yi Ma. A scholar is included among the top collaborators of Yi Ma 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 Yi Ma. Yi Ma 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.
Wang, Peng, Guowu Yuan, Z. Y. Zhang, et al.. (2025). Detection of Cotter Pin Defects in Transmission Lines Based on Improved YOLOv8. Electronics. 14(7). 1360–1360. 2 indexed citations
2.
Duan, Peiqi, et al.. (2025). EventAid: Benchmarking Event-Aided Image/Video Enhancement Algorithms With Real-Captured Hybrid Dataset. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(8). 6959–6973. 2 indexed citations
3.
Ma, Yi, Peng Duan, Chu Zhou, et al.. (2024). Color4E: Event Demosaicing for Full-color Event Guided Image Deblurring. 661–670. 1 indexed citations
4.
Yang, Lihua, et al.. (2024). Working together: an RACM model of policy implementation capacity. 4(1). 56–85. 1 indexed citations
5.
Liang, Hebin, et al.. (2023). SplitNet: A Reinforcement Learning Based Sequence Splitting Method for the MinMax Multiple Travelling Salesman Problem. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8720–8727. 4 indexed citations
6.
Zhou, Fangrong, Yi Ma, Yifan Wang, et al.. (2023). Multilevel feature cooperative alignment and fusion for unsupervised domain adaptation smoke detection. Frontiers in Physics. 11. 2 indexed citations
7.
Zhou, Fangrong, Gang Wen, Yi Ma, et al.. (2023). A two-branch cloud detection algorithm based on the fusion of a feature enhancement module and Gaussian mixture model. Mathematical Biosciences & Engineering. 20(12). 21588–21610.
8.
Jiang, Wei, et al.. (2022). Image Quality Assessment with Transformers and Multi-Metric Fusion Modules. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 1804–1808. 4 indexed citations
9.
Hu, Yabin, Guangbo Ren, Yi Ma, et al.. (2022). Coastal wetland hyperspectral classification under the collaborative of subspace partition and infinite probabilistic latent graph ranking. Science China Technological Sciences. 65(4). 759–777. 2 indexed citations
10.
Ma, Yi, Jianye Hao, Jiawen Lu, et al.. (2021). A Hierarchical Reinforcement Learning Based Optimization Framework for Large-scale Dynamic Pickup and Delivery Problems. Neural Information Processing Systems. 34. 39 indexed citations
11.
Hou, Fang, Yi Ma, Zheng Hu, et al.. (2021). Machine Learning Enabled Quickly Predicting of Detonation Properties of N‐Containing Molecules for Discovering New Energetic Materials. Advanced Theory and Simulations. 4(6). 18 indexed citations
12.
Liu, Leilei, Yi Ma, Haiyin Piao, et al.. (2020). Combining sequence and network information to enhance protein–protein interaction prediction. BMC Bioinformatics. 21(S16). 537–537. 32 indexed citations
13.
14.
Huang, Qi, et al.. (2018). Occult Spastic Diplegic Cerebral Palsy Recognition Using Efficient Machine Learning for Big Data and Structural Connectivity Abnormalities Analysis. Journal of Medical Imaging and Health Informatics. 8(2). 317–324. 6 indexed citations
15.
Ma, Yi, et al.. (2015). Image and spectral fidelity study of hyperspectral remote sensing image scaling up based on wavelet transform. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9669. 96690A–96690A. 1 indexed citations
16.
Yao, Cong, Xiang Bai, Wenyu Liu, Yi Ma, & Zhuowen Tu. (2012). Detecting texts of arbitrary orientations in natural images. 1083–1090. 505 indexed citations breakdown →
17.
Ma, Yi. (2003). A New Approach to Diagnosing Signals from Multivariate EWMA Control Chart.
18.
Ma, Yi. (2001). Process Capability Index for Multivariate Quality Characteristics. 1 indexed citations
19.
Ma, Yi, et al.. (1998). Static and dynamic characterization of magnetically actuated CMOS-micromachined cantilever-in-cantilever devices. Canadian Journal of Physics. 76(10). 747–758. 6 indexed citations
20.
Ma, Yi, et al.. (1997). SmartATMS. 1199–1205. 5 indexed citations

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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