Qihang Yu

6.3k total citations · 1 hit paper
20 papers, 991 citations indexed

About

Qihang Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Qihang Yu has authored 20 papers receiving a total of 991 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Qihang Yu's work include Advanced Neural Network Applications (10 papers), Medical Image Segmentation Techniques (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Qihang Yu is often cited by papers focused on Advanced Neural Network Applications (10 papers), Medical Image Segmentation Techniques (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Qihang Yu collaborates with scholars based in United States, China and South Korea. Qihang Yu's co-authors include Alan Yuille, Yuyin Zhou, Yixiao Zhang, Daguang Xu, Elliot K. Fishman, Lingxi Xie, Ziyue Xu, Xiaosong Wang, Yan Wang and Yutong Bai and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Medical Image Analysis and ACS Biomaterials Science & Engineering.

In The Last Decade

Qihang Yu

20 papers receiving 958 citations

Hit Papers

TransUNet: Rethinking the U-Net architecture design for m... 2024 2026 2025 2024 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. TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers
    2024 287 citations Jieneng Chen, Jieru Mei et al. Medical Image Analysis profile →

Peers

Qihang Yu
Zhe Liu China
Amirhossein Kazerouni Iran
Saeid Asgari Taghanaki Canada
Salman Khan United States
Ehsan Khodapanah Aghdam Germany
Bingzhi Chen China
Samir S. Yadav India
Qiangguo Jin China
Zhe Liu China
Qihang Yu
Citations per year, relative to Qihang Yu Qihang Yu (= 1×) peers Zhe Liu

Countries citing papers authored by Qihang Yu

Since Specialization
Citations

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

Fields of papers citing papers by Qihang Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qihang Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Qihang Yu. A scholar is included among the top collaborators of Qihang Yu 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 Qihang Yu. Qihang Yu 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.
Chen, Jieneng, Jieru Mei, Xianhang Li, et al.. (2024). TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformers. Medical Image Analysis. 97. 103280–103280. 287 indexed citations breakdown →
2.
Chen, Jieneng, Qihang Yu, Xiaohui Shen, Alan Yuille, & Liang-Chieh Chen. (2024). ViTamin: Designing Scalable Vision Models in the Vision-Language Era. 12954–12966. 12 indexed citations
3.
Deng, Xueqing, et al.. (2024). COCONut: Modernizing COCO Segmentation. 21863–21873. 2 indexed citations
4.
Shin, Inkyu, Dahun Kim, Qihang Yu, et al.. (2024). Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation. 228–238. 5 indexed citations
5.
He, Ju, et al.. (2023). Compositor: Bottom-Up Clustering and Compositing for Robust Part and Object Segmentation. 11259–11268. 1 indexed citations
6.
Kim, Dahun, Jun Xie, Huiyu Wang, et al.. (2022). TubeFormer-DeepLab: Video Mask Transformer. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 22 indexed citations
7.
Zhang, Jiao, Huijie Liu, Qihang Yu, et al.. (2022). Hair Derived Microneedle Patches for Both Diabetic Foot Ulcer Prevention and Healing. ACS Biomaterials Science & Engineering. 9(1). 363–374. 16 indexed citations
8.
Lu, Weidong, Chunguo Zhang, & Qihang Yu. (2022). Stress intensity-dependent relation between overload plastic zone and fatigue retardation in Al-alloy. Theoretical and Applied Fracture Mechanics. 121. 103520–103520. 5 indexed citations
9.
Yu, Qihang, Huiyu Wang, Dahun Kim, et al.. (2022). CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2550–2560. 55 indexed citations
10.
Yu, Qihang, Jianming Zhang, He Zhang, et al.. (2021). Mask Guided Matting via Progressive Refinement Network. 1154–1163. 58 indexed citations
11.
Liu, Yiming, et al.. (2021). HelpCloud: Hierarchy Health Evaluation for Private Cloud. Journal of Physics Conference Series. 1738(1). 12008–12008. 1 indexed citations
12.
Yu, Qihang, Yingwei Li, Jieru Mei, Yuyin Zhou, & Alan Yuille. (2021). CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 35(4). 3225–3233. 2 indexed citations
13.
Yu, Qihang, Dong Yang, Holger R. Roth, et al.. (2020). C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation. 4125–4134. 89 indexed citations
14.
Zhang, Yixiao, Xiaosong Wang, Ziyue Xu, et al.. (2020). When Radiology Report Generation Meets Knowledge Graph. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 12910–12917. 196 indexed citations
15.
Yu, Qihang, Yingda Xia, Lingxi Xie, Elliot K. Fishman, & Alan Yuille. (2019). Thickened 2D Networks for 3D Medical Image Segmentation.. arXiv (Cornell University). 3 indexed citations
16.
Xie, Lingxi, Qihang Yu, Yuyin Zhou, et al.. (2019). Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans. IEEE Transactions on Medical Imaging. 39(2). 514–525. 62 indexed citations
17.
Yu, Qihang, Lingxi Xie, Yan Wang, et al.. (2018). Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation. 8280–8289. 171 indexed citations
18.
Yu, Qihang, Lingxi Xie, Yan Wang, et al.. (2017). Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Pancreas Segmentation.. arXiv (Cornell University). 1 indexed citations
19.
Yu, Qihang, et al.. (2015). A reconfigurable parallel FPGA accelerator for the kernel affine projection algorithm. 906–910. 1 indexed citations
20.
Yu, Qihang, et al.. (2015). A real-time permutation entropy computation for EEG signals. 20–21. 2 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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