Yimian Dai

3.3k total citations · 3 hit papers
26 papers, 2.2k citations indexed

About

Yimian Dai is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition and Mechanics of Materials. According to data from OpenAlex, Yimian Dai has authored 26 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Aerospace Engineering, 9 papers in Computer Vision and Pattern Recognition and 8 papers in Mechanics of Materials. Recurrent topics in Yimian Dai's work include Infrared Target Detection Methodologies (17 papers), Thermography and Photoacoustic Techniques (8 papers) and Image and Signal Denoising Methods (3 papers). Yimian Dai is often cited by papers focused on Infrared Target Detection Methodologies (17 papers), Thermography and Photoacoustic Techniques (8 papers) and Image and Signal Denoising Methods (3 papers). Yimian Dai collaborates with scholars based in China, United States and Denmark. Yimian Dai's co-authors include Yiquan Wu, Kobus Barnard, Fei Zhou, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, Yu Song, Jian Yang, Xiang Li and Yiquan Wu and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Access and Remote Sensing.

In The Last Decade

Yimian Dai

25 papers receiving 2.2k citations

Hit Papers

Attentional Feature Fusion 2017 2026 2020 2023 2021 2021 2017 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yimian Dai China 12 1.5k 972 547 498 437 26 2.2k
Yongtao Wang China 19 1.1k 0.7× 701 0.7× 1.5k 2.7× 528 1.1× 245 0.6× 107 2.8k
Chenqiang Gao China 24 1.3k 0.9× 920 0.9× 1.4k 2.6× 773 1.6× 335 0.8× 113 3.1k
Yiquan Wu China 11 1.4k 1.0× 923 0.9× 399 0.7× 408 0.8× 417 1.0× 25 1.8k
Yulan Guo China 15 897 0.6× 448 0.5× 554 1.0× 189 0.4× 125 0.3× 74 1.6k
Longguang Wang China 23 694 0.5× 488 0.5× 1.5k 2.8× 873 1.8× 123 0.3× 73 2.4k
Fei Zhou China 12 699 0.5× 476 0.5× 395 0.7× 244 0.5× 172 0.4× 35 1.3k
Changcai Yang China 18 427 0.3× 210 0.2× 517 0.9× 286 0.6× 60 0.1× 73 1.1k
Shuhui Bu China 27 468 0.3× 226 0.2× 1.6k 2.9× 885 1.8× 67 0.2× 90 2.6k
Ji‐Hoon Bae South Korea 17 498 0.3× 280 0.3× 732 1.3× 253 0.5× 45 0.1× 88 1.7k
Yanpeng Cao China 23 341 0.2× 144 0.1× 1.1k 1.9× 505 1.0× 185 0.4× 82 1.9k

Countries citing papers authored by Yimian Dai

Since Specialization
Citations

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

Fields of papers citing papers by Yimian Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yimian Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Yimian Dai. A scholar is included among the top collaborators of Yimian Dai 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 Yimian Dai. Yimian Dai 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.
Zhou, Fei, Fengyi Wu, Maixia Fu, et al.. (2025). DRPCA-Net: Make Robust PCA Great Again for Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–16. 2 indexed citations
2.
Sun, Yang, Zaiping Lin, Ting Liu, et al.. (2025). Infrared Small Target Detection via Nonconvex Weighted Tensor Rank Minimization and Adaptive Spatial–Temporal Modeling. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–18. 1 indexed citations
3.
Dai, Qun, Yimian Dai, Yuxuan Li, et al.. (2025). MoCoLSK: Modality-Conditioned High-Resolution Downscaling for Land Surface Temperature. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–17. 1 indexed citations
4.
Zhao, Jinmiao, Zelin Shi, Chuang Yu, et al.. (2025). Multi-Scale Direction-Aware Network for Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–18. 1 indexed citations
5.
Dai, Yimian, et al.. (2024). DenoDet: Attention as Deformable Multisubspace Feature Denoising for Target Detection in SAR Images. IEEE Transactions on Aerospace and Electronic Systems. 61(2). 4729–4743. 6 indexed citations
6.
Dai, Yimian, et al.. (2024). Pick of the Bunch: Detecting Infrared Small Targets Beyond Hit-Miss Trade-Offs via Selective Rank-Aware Attention. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 11 indexed citations
7.
Zhou, Fei, et al.. (2024). Sparse Prior Is Not All You Need: When Differential Directionality Meets Saliency Coherence for Infrared Small Target Detection. IEEE Transactions on Instrumentation and Measurement. 73. 1–18. 3 indexed citations
8.
Zhang, Feifei, et al.. (2024). Display method for high dynamic range infrared image based on gradient domain guided image filter. Optical Engineering. 63(1). 2 indexed citations
9.
Zhang, Feifei, et al.. (2023). Brightness segmentation-based plateau histogram equalization algorithm for displaying high dynamic range infrared images. Infrared Physics & Technology. 134. 104894–104894. 10 indexed citations
10.
Dai, Yimian, et al.. (2023). One-Stage Cascade Refinement Networks for Infrared Small Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–17. 80 indexed citations
11.
Dai, Yimian, Yiquan Wu, Fei Zhou, & Kobus Barnard. (2021). Asymmetric Contextual Modulation for Infrared Small Target Detection. 949–958. 475 indexed citations breakdown →
12.
Dai, Yimian, Stefan Oehmcke, Fabian Gieseke, Yiquan Wu, & Kobus Barnard. (2021). Attention as Activation. Research at the University of Copenhagen (University of Copenhagen). 9156–9163. 6 indexed citations
13.
Dai, Yimian, Fabian Gieseke, Stefan Oehmcke, Yiquan Wu, & Kobus Barnard. (2021). Attentional Feature Fusion. Research at the University of Copenhagen (University of Copenhagen). 3559–3568. 696 indexed citations breakdown →
15.
Zhou, Fei, et al.. (2019). Graph-Regularized Laplace Approximation for Detecting Small Infrared Target Against Complex Backgrounds. IEEE Access. 7. 85354–85371. 18 indexed citations
16.
Wu, Yiquan, et al.. (2017). Small target detection based on reweighted infrared patch‐image model. IET Image Processing. 12(1). 70–79. 74 indexed citations
17.
Dai, Yimian & Yiquan Wu. (2017). Reweighted Infrared Patch-Tensor Model With Both Nonlocal and Local Priors for Single-Frame Small Target Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 10(8). 3752–3767. 408 indexed citations breakdown →
18.
Wu, Yiquan, et al.. (2016). Automatic river target detection from remote sensing images based on image decomposition and distance regularized CV model. Computers & Electrical Engineering. 54. 285–295. 4 indexed citations
19.
Wu, Yiquan, Yimian Dai, Jun Yin, & Jian Wu. (2015). Fast non-local means algorithm based on Krawtchouk moments. Transactions of Tianjin University. 21(2). 104–112. 2 indexed citations
20.
Song, Yu, Yiquan Wu, & Yimian Dai. (2015). A new active contour remote sensing river image segmentation algorithm inspired from the cross entropy. Digital Signal Processing. 48. 322–332. 40 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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