Fengze Liu

1.4k total citations · 1 hit paper
10 papers, 473 citations indexed

About

Fengze Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Organic Chemistry. According to data from OpenAlex, Fengze Liu has authored 10 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Organic Chemistry. Recurrent topics in Fengze Liu's work include Advanced Neural Network Applications (5 papers), Medical Image Segmentation Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Fengze Liu is often cited by papers focused on Advanced Neural Network Applications (5 papers), Medical Image Segmentation Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Fengze Liu collaborates with scholars based in United States, China and Hong Kong. Fengze Liu's co-authors include Alan Yuille, Daguang Xu, Yingda Xia, Dong Yang, Jinzheng Cai, Lequan Yu, Holger R. Roth, Zhuotun Zhu, Wei Shen and Yiming Liu and has published in prestigious journals such as Medical Image Analysis, Journal of the American Oil Chemists Society and Agriculture.

In The Last Decade

Fengze Liu

9 papers receiving 469 citations

Hit Papers

Intriguing Findings of Frequency Selection for Image Debl... 2023 2026 2024 2025 2023 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fengze Liu United States 6 319 171 148 78 46 10 473
Yin Dai China 9 214 0.7× 156 0.9× 162 1.1× 62 0.8× 41 0.9× 14 455
Cheng Bian China 12 228 0.7× 225 1.3× 224 1.5× 60 0.8× 22 0.5× 21 487
Rajeshwar Dass India 9 164 0.5× 136 0.8× 131 0.9× 56 0.7× 79 1.7× 28 394
Zhuotun Zhu United States 9 424 1.3× 266 1.6× 253 1.7× 68 0.9× 13 0.3× 11 613
Ceyhun Burak Akgül Türkiye 11 380 1.2× 96 0.6× 118 0.8× 44 0.6× 34 0.7× 27 525
Kamel Hamrouni Tunisia 11 209 0.7× 120 0.7× 149 1.0× 23 0.3× 39 0.8× 68 382
He Cheng United States 7 346 1.1× 182 1.1× 275 1.9× 33 0.4× 116 2.5× 19 544
Gabriel Efrain Humpire Mamani Netherlands 5 141 0.4× 86 0.5× 78 0.5× 47 0.6× 22 0.5× 6 282
Kongming Liang China 10 203 0.6× 92 0.5× 169 1.1× 41 0.5× 26 0.6× 36 378
Fengbei Liu Australia 6 177 0.6× 104 0.6× 176 1.2× 23 0.3× 30 0.7× 10 333

Countries citing papers authored by Fengze Liu

Since Specialization
Citations

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

Fields of papers citing papers by Fengze Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fengze Liu

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

All Works

10 of 10 papers shown
2.
Zhou, Yuyin, Xianhang Li, Fengze Liu, et al.. (2024). L2B: Learning to Bootstrap Robust Models for Combating Label Noise. 23523–23533. 1 indexed citations
3.
Liu, Yiming, et al.. (2023). Intriguing Findings of Frequency Selection for Image Deblurring. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 1905–1913. 102 indexed citations breakdown →
4.
Zhang, Haibo, Fengze Liu, Jiali Ren, et al.. (2022). A Multiplex PCR System for the Screening of Genetically Modified (GM) Maize and the Detection of 29 GM Maize Events Based on Capillary Electrophoresis. Agriculture. 12(3). 413–413. 5 indexed citations
5.
Xia, Yingda, Dong Yang, Zhiding Yu, et al.. (2020). Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation. Medical Image Analysis. 65. 101766–101766. 163 indexed citations
6.
Wang, Yan, Wei Xu, Fengze Liu, et al.. (2020). Deep Distance Transform for Tubular Structure Segmentation in CT Scans. 3832–3841. 76 indexed citations
7.
Xia, Yingda, Fengze Liu, Dong Yang, et al.. (2020). 3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training. 3635–3644. 93 indexed citations
8.
Liu, Fengze, Yingda Xia, Dong Yang, Alan Yuille, & Daguang Xu. (2019). An Alarm System for Segmentation Algorithm Based on Shape Model. 10651–10660. 10 indexed citations
9.
Xia, Yingda, Lingxi Xie, Fengze Liu, et al.. (2018). Bridging the Gap Between 2D and 3D Organ Segmentation.. arXiv (Cornell University). 2 indexed citations
10.
He, Wenhao, et al.. (2010). Optimization of Supercritical Carbon Dioxide Extraction of Gardenia Fruit Oil and the Analysis of Functional Components. Journal of the American Oil Chemists Society. 87(9). 1071–1079. 21 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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