Fengwei Yu

2.9k total citations · 1 hit paper
18 papers, 1.2k citations indexed

About

Fengwei Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Fengwei Yu has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Fengwei Yu's work include Advanced Neural Network Applications (14 papers), Domain Adaptation and Few-Shot Learning (11 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Fengwei Yu is often cited by papers focused on Advanced Neural Network Applications (14 papers), Domain Adaptation and Few-Shot Learning (11 papers) and Advanced Image and Video Retrieval Techniques (7 papers). Fengwei Yu collaborates with scholars based in China, United States and Australia. Fengwei Yu's co-authors include Ruihao Gong, Xianglong Liu, Aojun Zhou, Ziwei Liu, Wei Wu, Kun Yuan, Shaopeng Guo, Junjie Yan, Haotong Qin and Mingzhu Shen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Signal Processing and International Journal of Computer Vision.

In The Last Decade

Fengwei Yu

17 papers receiving 1.1k citations

Hit Papers

Incorporating Convolution Designs into Visual Transformers 2021 2026 2022 2024 2021 100 200 300
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. Incorporating Convolution Designs into Visual Transformers
    2021 373 citations Kun Yuan, Shaopeng Guo et al. 2021 IEEE/CVF International Conference on Computer Vision (ICCV) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fengwei Yu China 11 822 534 165 136 73 18 1.2k
Bohan Zhuang Australia 19 1.1k 1.3× 648 1.2× 164 1.0× 92 0.7× 82 1.1× 42 1.5k
Yizeng Han China 12 559 0.7× 361 0.7× 141 0.9× 113 0.8× 80 1.1× 22 1.0k
Ruihao Gong China 14 751 0.9× 666 1.2× 257 1.6× 76 0.6× 50 0.7× 34 1.2k
Peizhao Zhang United States 14 1.4k 1.7× 825 1.5× 224 1.4× 73 0.5× 75 1.0× 28 1.9k
Jian-Hao Luo China 6 1.4k 1.8× 1.0k 1.9× 136 0.8× 89 0.7× 52 0.7× 9 1.8k
Aojun Zhou China 10 509 0.6× 298 0.6× 103 0.6× 92 0.7× 56 0.8× 25 748
Zhen Dong China 17 732 0.9× 408 0.8× 366 2.2× 192 1.4× 52 0.7× 43 1.2k
Xiaoyi Dong China 11 1.0k 1.2× 504 0.9× 161 1.0× 252 1.9× 136 1.9× 26 1.6k
Mingbao Lin China 18 1.1k 1.4× 748 1.4× 97 0.6× 88 0.6× 59 0.8× 42 1.4k
Byeongho Heo South Korea 13 809 1.0× 678 1.3× 51 0.3× 61 0.4× 44 0.6× 26 1.2k

Countries citing papers authored by Fengwei Yu

Since Specialization
Citations

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

Fields of papers citing papers by Fengwei Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengwei Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Fengwei Yu. A scholar is included among the top collaborators of Fengwei 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 Fengwei Yu. Fengwei Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Yang, Hailong, Fengwei Yu, Ruihao Gong, et al.. (2023). Exploiting Subgraph Similarities for Efficient Auto-tuning of Tensor Programs. 786–796. 2 indexed citations
2.
Bai, Lei, et al.. (2023). Towards Frame Rate Agnostic Multi-object Tracking. International Journal of Computer Vision. 132(5). 1443–1462. 5 indexed citations
3.
Tan, Jingru, Bo Li, Yongqiang Yao, et al.. (2023). The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(11). 13876–13892. 15 indexed citations
4.
Li, Bo, Yongqiang Yao, Jingru Tan, et al.. (2022). Equalized Focal Loss for Dense Long-Tailed Object Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6980–6989. 86 indexed citations
5.
Liu, Liang, Mingzhu Shen, Ruihao Gong, Fengwei Yu, & Hailong Yang. (2022). NNLQP: A Multi-Platform Neural Network Latency Query and Prediction System with An Evolving Database. 1–14. 8 indexed citations
6.
Li, Yuhang, Ruihao Gong, Xu Tan, et al.. (2021). BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction. arXiv (Cornell University). 14 indexed citations
7.
Shen, Mingzhu, Feng Liang, Ruihao Gong, et al.. (2021). Once Quantization-Aware Training: High Performance Extremely Low-bit Architecture Search. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 5320–5329. 17 indexed citations
8.
Wang, Yan, et al.. (2021). Real World Robustness from Systematic Noise. 42–48. 2 indexed citations
9.
Li, Yuhang, Feng Zhu, Ruihao Gong, et al.. (2021). MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4390–4399. 16 indexed citations
10.
Yuan, Kun, Shaopeng Guo, Ziwei Liu, et al.. (2021). Incorporating Convolution Designs into Visual Transformers. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 559–568. 373 indexed citations breakdown →
11.
Zhang, Xiangguo, Haotong Qin, Yifu Ding, et al.. (2021). Diversifying Sample Generation for Accurate Data-Free Quantization. 15653–15662. 53 indexed citations
12.
Zhu, Feng, Ruihao Gong, Fengwei Yu, et al.. (2020). Towards Unified INT8 Training for Convolutional Neural Network. 1966–1976. 99 indexed citations
13.
Qin, Haotong, Ruihao Gong, Xianglong Liu, et al.. (2020). Forward and Backward Information Retention for Accurate Binary Neural Networks. 2247–2256. 205 indexed citations
14.
Yu, Fengwei, Hailong Yang, Bing Liu, et al.. (2020). Extremely Low-bit Convolution Optimization for Quantized Neural Network on Modern Computer Architectures. 1–12. 11 indexed citations
15.
Gong, Ruihao, Xianglong Liu, Tianxiang Li, et al.. (2019). Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks. 4851–4860. 247 indexed citations
16.
Qin, Haotong, Ruihao Gong, Xianglong Liu, et al.. (2019). IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks. arXiv (Cornell University). 5 indexed citations
17.
Zhuang, Xinhua, Yan Huang, & Fengwei Yu. (1994). Design of Hopfield content-addressable memories. IEEE Transactions on Signal Processing. 42(2). 492–495. 9 indexed citations
18.
Zhuang, Xinhua, Yan Huang, Fengwei Yu, & Peng Zhang. (1994). A neural net algorithm for multidimensional minimum relative-entropy spectral analysis. IEEE Transactions on Signal Processing. 42(2). 489–491.

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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