Dawei Qi

5.6k total citations · 3 hit papers
144 papers, 4.7k citations indexed

About

Dawei Qi is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Spectroscopy. According to data from OpenAlex, Dawei Qi has authored 144 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Vision and Pattern Recognition, 23 papers in Industrial and Manufacturing Engineering and 21 papers in Spectroscopy. Recurrent topics in Dawei Qi's work include Image Processing and 3D Reconstruction (27 papers), Industrial Vision Systems and Defect Detection (23 papers) and Advanced Proteomics Techniques and Applications (15 papers). Dawei Qi is often cited by papers focused on Image Processing and 3D Reconstruction (27 papers), Industrial Vision Systems and Defect Detection (23 papers) and Advanced Proteomics Techniques and Applications (15 papers). Dawei Qi collaborates with scholars based in China, Singapore and United States. Dawei Qi's co-authors include Chunhui Deng, Xiangmin Zhang, Dongyuan Zhao, Yonghui Deng, Abhik Roychoudhury, Satish Chandra, Jin Lü, Pengyuan Yang, Jia Tang and Pengyuan Yang and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and Bioinformatics.

In The Last Decade

Dawei Qi

136 papers receiving 4.6k citations

Hit Papers

Superparamagnetic High-Ma... 2007 2026 2013 2019 2007 2013 2013 500 1000 1.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Dawei Qi 1.3k 999 840 824 739 144 4.7k
Wen Zhang 1.9k 1.5× 1.8k 1.8× 433 0.5× 2.0k 2.5× 751 1.0× 232 7.1k
Bo Li 2.1k 1.7× 419 0.4× 169 0.2× 1.9k 2.4× 545 0.7× 238 6.3k
David Gray 1.2k 0.9× 352 0.4× 99 0.1× 1.3k 1.6× 459 0.6× 111 4.3k
Jiang Wang 1.0k 0.8× 584 0.6× 154 0.2× 183 0.2× 289 0.4× 83 3.1k
Chia‐Wei Wang 1.5k 1.2× 1.4k 1.4× 226 0.3× 586 0.7× 101 0.1× 58 3.8k
Li Chen 1.1k 0.8× 518 0.5× 185 0.2× 1.6k 2.0× 218 0.3× 203 6.3k
Ji Yang 1.8k 1.4× 142 0.1× 229 0.3× 669 0.8× 303 0.4× 215 5.3k
Ka Ming Ng 2.3k 1.8× 391 0.4× 394 0.5× 1.2k 1.5× 319 0.4× 222 6.3k
Dongwoo Kim 1.7k 1.3× 389 0.4× 830 1.0× 281 0.3× 1.7k 2.3× 137 4.7k
Hong Liang 3.6k 2.8× 2.8k 2.8× 464 0.6× 2.5k 3.0× 2.8k 3.7× 515 11.6k

Countries citing papers authored by Dawei Qi

Since Specialization
Citations

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

Fields of papers citing papers by Dawei Qi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dawei Qi

This figure shows the co-authorship network connecting the top 25 collaborators of Dawei Qi. A scholar is included among the top collaborators of Dawei Qi 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 Dawei Qi. Dawei Qi 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.
Li, Guoxin, et al.. (2024). Plant-Leaf Recognition Based on Sample Standardization and Transfer Learning. Applied Sciences. 14(18). 8122–8122. 1 indexed citations
2.
Han, Yu, et al.. (2023). Preparation of Superhydrophobic Wood Surfaces Modified Using MIL-88(Fe) via Solvothermal Method. Forests. 14(9). 1772–1772. 2 indexed citations
3.
Wu, Xiaoxia, Jie Xing, Ruifen Zou, et al.. (2023). Using host–guest interactions at the interface of quantum dots to load drug molecules for biocompatible, safe, and effective chemo-photodynamic therapy against cancer. Journal of Materials Chemistry B. 11(22). 4855–4864. 9 indexed citations
4.
Wan, Zihao, et al.. (2023). BO-densenet: A bilinear one-dimensional densenet network based on multi-scale feature fusion for wood NIR classification. Chemometrics and Intelligent Laboratory Systems. 240. 104920–104920. 5 indexed citations
5.
Gao, Mingyu, Peng Song, Fei Wang, et al.. (2021). A Novel Deep Convolutional Neural Network Based on ResNet‐18 and Transfer Learning for Detection of Wood Knot Defects. Journal of Sensors. 2021(1). 30 indexed citations
6.
Gao, Mingyu, Fei Wang, Peng Song, Junyan Liu, & Dawei Qi. (2021). BLNN: Multiscale Feature Fusion‐Based Bilinear Fine‐Grained Convolutional Neural Network for Image Classification of Wood Knot Defects. Journal of Sensors. 2021(1). 13 indexed citations
7.
Gao, Ling, et al.. (2019). New versatile zincic sorbent for tobacco specific nitrosamines and lead ion capture. Journal of Hazardous Materials. 383. 121188–121188. 7 indexed citations
8.
Mu, Hongbo, Mingming Zhang, Dawei Qi, et al.. (2014). Detection and recognition of wood defects based on gray transformation and BP neural network.. International journal of agriculture innovation and research. 2(6). 1079–1083. 1 indexed citations
9.
Qi, Dawei, et al.. (2013). SemFix: Program repair via semantic analysis. 2013 35th International Conference on Software Engineering (ICSE). 772–781. 249 indexed citations breakdown →
10.
Qi, Dawei. (2013). Mathematic Modelling and Simulation of a Two-way Electro-hydraulic Proportional Flow Valve. Machine Tool & Hydraulics. 1 indexed citations
11.
Qi, Dawei, et al.. (2013). SemFix: program repair via semantic analysis. International Conference on Software Engineering. 772–781. 264 indexed citations breakdown →
12.
Qi, Dawei, et al.. (2010). Edge detection of wood defects in X-ray wood image using neural network and mathematical morphology. Chinese Control Conference. 2375–2380. 1 indexed citations
13.
14.
Qi, Dawei, Jin Lü, Chunhui Deng, & Xiangmin Zhang. (2009). Development of core–shell structure Fe3O4@Ta2O5 microspheres for selective enrichment of phosphopeptides for mass spectrometry analysis. Journal of Chromatography A. 1216(29). 5533–5539. 62 indexed citations
15.
Qi, Dawei, Yu Mao, Jin Lü, Chunhui Deng, & Xiangmin Zhang. (2009). Phosphate-functionalized magnetic microspheres for immobilization of Zr4+ ions for selective enrichment of the phosphopeptides. Journal of Chromatography A. 1217(16). 2606–2617. 56 indexed citations
16.
Tang, Jia, Yingchao Liu, Dawei Qi, et al.. (2009). On‐plate‐selective enrichment of glycopeptides using boronic acid‐modified gold nanoparticles for direct MALDI‐QIT‐TOF MS analysis. PROTEOMICS. 9(22). 5046–5055. 105 indexed citations
17.
Qi, Dawei. (2008). Edge Detection Algorithm’s Research of X-Ray Medical Image Based On Canny Operator. Liaoning Zhongyiyao Daxue xuebao. 1 indexed citations
19.
Yao, Guoping, Dawei Qi, Chunhui Deng, & Xiangmin Zhang. (2008). Functionalized magnetic carbonaceous microspheres for trypsin immobilization and the application to fast proteolysis. Journal of Chromatography A. 1215(1-2). 82–91. 33 indexed citations
20.
Qi, Dawei. (2007). Log Image Edge Detection Method Based on Multi-Scale Mathematical Morphology. 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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