Feiwei Qin

2.1k total citations · 1 hit paper
91 papers, 1.3k citations indexed

About

Feiwei Qin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Feiwei Qin has authored 91 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 16 papers in Computational Mechanics. Recurrent topics in Feiwei Qin's work include 3D Shape Modeling and Analysis (13 papers), Face and Expression Recognition (8 papers) and Manufacturing Process and Optimization (7 papers). Feiwei Qin is often cited by papers focused on 3D Shape Modeling and Analysis (13 papers), Face and Expression Recognition (8 papers) and Manufacturing Process and Optimization (7 papers). Feiwei Qin collaborates with scholars based in China, Hong Kong and United Kingdom. Feiwei Qin's co-authors include Yong Peng, Wanzeng Kong, Yanli Shao, Shuming Gao, Yang Chen, Guojun Dai, Jianhai Zhang, Jing Bai, Hong Zeng and Changmiao Wang and has published in prestigious journals such as Scientific Reports, Cancer Letters and Sustainability.

In The Last Decade

Feiwei Qin

76 papers receiving 1.3k citations

Hit Papers

Accurate leukocyte detection based on deformable-DETR and... 2024 2026 2025 2024 50 100 150
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. Accurate leukocyte detection based on deformable-DETR and multi-level feature fusion for aiding diagnosis of blood diseases
    2024 163 citations Chenyan Zhang, Yiyu Huang 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
Feiwei Qin China 20 502 279 248 181 177 91 1.3k
Yong Peng China 25 582 1.2× 589 2.1× 685 2.8× 66 0.4× 524 3.0× 137 2.0k
Wenqiang Zhang China 22 1.2k 2.3× 610 2.2× 148 0.6× 67 0.4× 280 1.6× 124 2.1k
Anikó Ekárt United Kingdom 16 175 0.3× 313 1.1× 205 0.8× 99 0.5× 80 0.5× 71 1.2k
Shang‐Hong Lai Taiwan 28 2.5k 5.0× 268 1.0× 141 0.6× 138 0.8× 224 1.3× 230 3.2k
Mohammad Farukh Hashmi India 19 552 1.1× 273 1.0× 87 0.4× 65 0.4× 40 0.2× 94 1.2k
Reza Ebrahimpour Iran 21 473 0.9× 458 1.6× 618 2.5× 44 0.2× 55 0.3× 139 2.0k
Yongbin Gao China 20 631 1.3× 171 0.6× 67 0.3× 34 0.2× 47 0.3× 88 1.3k
Shijie Hao China 19 1.0k 2.1× 524 1.9× 108 0.4× 65 0.4× 93 0.5× 65 1.9k
Khoa Luu United States 19 1.1k 2.3× 412 1.5× 79 0.3× 32 0.2× 87 0.5× 94 1.7k

Countries citing papers authored by Feiwei Qin

Since Specialization
Citations

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

Fields of papers citing papers by Feiwei Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feiwei Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Feiwei Qin. A scholar is included among the top collaborators of Feiwei Qin 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 Feiwei Qin. Feiwei Qin 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.
Zong, Jie, et al.. (2026). Towards practical Alzheimer’s Disease diagnosis: A lightweight and interpretable spiking neural model. Biomedical Signal Processing and Control. 117. 109595–109595.
2.
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Li, Jinghui, Wen Zhang, Zhen Qian, et al.. (2025). Physical Modeling of High-Pressure Flooding and Development of Oil Displacement Agent for Carbonate Fracture-Vuggy Reservoir. Processes. 13(1). 71–71. 1 indexed citations
4.
Qin, Feiwei, et al.. (2025). Spatial proximity, enterprise agglomeration, and innovation output: Mechanisms and insights from China. Sustainable Futures. 9. 100793–100793.
5.
Fan, Jin, et al.. (2025). Path-aware multi-scale learning for heterogeneous graph neural network. Neural Networks. 191. 107743–107743. 1 indexed citations
6.
7.
Qin, Feiwei, Kang Yan, Changmiao Wang, et al.. (2024). LKFormer: large kernel transformer for infrared image super-resolution. Multimedia Tools and Applications. 83(28). 72063–72077. 11 indexed citations
8.
Qin, Feiwei, et al.. (2024). The Impact of High-Tech Policies on Corporate ESG Performance: Evidence from China. Sustainability. 16(23). 10321–10321.
9.
Wang, Zhen, et al.. (2024). Experimental and numerical investigation on the discrete fracture property and dynamic flexural response of aluminum nitride ceramics. Engineering Fracture Mechanics. 308. 110384–110384. 2 indexed citations
10.
Qin, Feiwei, et al.. (2024). ID-UNet: A densely connected UNet architecture for infrared small target segmentation. Alexandria Engineering Journal. 110. 234–244. 10 indexed citations
11.
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Qin, Feiwei, et al.. (2024). IDTransformer: Infrared image denoising method based on convolutional transposed self-attention. Alexandria Engineering Journal. 110. 310–321. 8 indexed citations
13.
Chen, Zhixiong, Ruiquan Ge, Changmiao Wang, et al.. (2024). Identification of important gene signatures in schizophrenia through feature fusion and genetic algorithm. Mammalian Genome. 35(2). 241–255. 1 indexed citations
14.
Zhu, Zhu, Yunpeng Zhu, Chenyan Zhang, et al.. (2024). SCKansformer: Fine-Grained Classification of Bone Marrow Cells via Kansformer Backbone and Hierarchical Attention Mechanisms. IEEE Journal of Biomedical and Health Informatics. 29(1). 558–571. 23 indexed citations
15.
Luo, Chenqi, et al.. (2023). FuS-GCN: Efficient B-rep based graph convolutional networks for 3D-CAD model classification and retrieval. Advanced Engineering Informatics. 56. 102008–102008. 39 indexed citations
16.
Peng, Yong, Wanzeng Kong, Feiwei Qin, et al.. (2021). Self-Weighted Semi-Supervised Classification for Joint EEG-Based Emotion Recognition and Affective Activation Patterns Mining. IEEE Transactions on Instrumentation and Measurement. 70. 1–11. 29 indexed citations
17.
Qin, Feiwei, et al.. (2021). Recurrent neural network from adder’s perspective: Carry-lookahead RNN. Neural Networks. 144. 297–306. 40 indexed citations
18.
Peng, Yong, Feiwei Qin, Wanzeng Kong, et al.. (2021). GFIL: A Unified Framework for the Importance Analysis of Features, Frequency Bands, and Channels in EEG-Based Emotion Recognition. IEEE Transactions on Cognitive and Developmental Systems. 14(3). 935–947. 64 indexed citations
19.
Qin, Feiwei, et al.. (2018). Integrated Modeling, Simulation, and Visualization for Nanomaterials. Complexity. 2018(1). 1 indexed citations
20.
Peng, Yong, Wanzeng Kong, Feiwei Qin, & Feiping Nie. (2018). Manifold Adaptive Kernelized Low‐Rank Representation for Semisupervised Image Classification. Complexity. 2018(1). 1 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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