Pengfei Dou

467 total citations
12 papers, 270 citations indexed

About

Pengfei Dou is a scholar working on Computer Vision and Pattern Recognition, Dermatology and Neurology. According to data from OpenAlex, Pengfei Dou has authored 12 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 2 papers in Dermatology and 2 papers in Neurology. Recurrent topics in Pengfei Dou's work include Face recognition and analysis (9 papers), Face and Expression Recognition (5 papers) and Biometric Identification and Security (2 papers). Pengfei Dou is often cited by papers focused on Face recognition and analysis (9 papers), Face and Expression Recognition (5 papers) and Biometric Identification and Security (2 papers). Pengfei Dou collaborates with scholars based in United States, China and Italy. Pengfei Dou's co-authors include Ioannis A. Kakadiaris, Shishir K. Shah, Xiang Xu, Lingfeng Zhang, Lei Yang, Zhijing Xie, Ruihua Zhang, Qian Xu, Linlin Chen and Jingxin Li and has published in prestigious journals such as Journal of Virology, IEEE Access and Pattern Recognition.

In The Last Decade

Pengfei Dou

12 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pengfei Dou United States	8	230	66	62	31	18	12	270
Matan Sela Israel	3	353 1.5×	154 2.3×	48 0.8×	50 1.6×	43 2.4×	6	373
Mingkai Huang China	5	230 1.0×	96 1.5×	35 0.6×	15 0.5×	25 1.4×	5	251
Alexandros Lattas United Kingdom	7	129 0.6×	50 0.8×	26 0.4×	9 0.3×	29 1.6×	13	164
Roy Or-El Israel	4	395 1.7×	177 2.7×	32 0.5×	24 0.8×	129 7.2×	4	417
Dalong Jiang China	5	262 1.1×	65 1.0×	64 1.0×	4 0.1×	8 0.4×	9	277
Zhaoyang Lyu China	5	117 0.5×	24 0.4×	5 0.1×	16 0.5×	16 0.9×	7	175
Georgios Passalis Greece	5	401 1.7×	49 0.7×	178 2.9×	5 0.2×	7 0.4×	6	423
Haozhi Huang China	9	235 1.0×	38 0.6×	22 0.4×	3 0.1×	45 2.5×	15	272
Shengju Qian Hong Kong	5	170 0.7×	8 0.1×	20 0.3×	6 0.2×	5 0.3×	8	190

Countries citing papers authored by Pengfei Dou

Since Specialization

Citations

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

Fields of papers citing papers by Pengfei Dou

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengfei Dou

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Zhao, Xi, et al.. (2019). 3D Face Reconstruction From Volumes of Videos Using a Mapreduce Framework. IEEE Access. 7. 165559–165570. 4 indexed citations

2.

Yuan, Rui, Yuanjiang Wang, Pengfei Dou, et al.. (2018). Synthesis and Biological Evaluation of Novel Flavonoid-Substituted Tröger's Bases. Chinese Journal of Organic Chemistry. 38(12). 3338–3338. 1 indexed citations

3.

Dou, Pengfei & Ioannis A. Kakadiaris. (2018). Multi-view 3D face reconstruction with deep recurrent neural networks. Image and Vision Computing. 80. 80–91. 28 indexed citations

4.

Dou, Pengfei, et al.. (2018). Monocular 3D facial shape reconstruction from a single 2D image with coupled-dictionary learning and sparse coding. Pattern Recognition. 81. 515–527. 7 indexed citations

5.

Dou, Pengfei, Shishir K. Shah, & Ioannis A. Kakadiaris. (2017). End-to-End 3D Face Reconstruction with Deep Neural Networks. 1503–1512. 151 indexed citations

6.

Dou, Pengfei & Ioannis A. Kakadiaris. (2017). Multi-view 3D face reconstruction with deep recurrent neural networks. 483–492. 8 indexed citations

7.

Xu, Xiang, et al.. (2017). Evaluation of a 3D-aided pose invariant 2D face recognition system. 10. 446–455. 21 indexed citations

8.

Dou, Pengfei, et al.. (2015). Pose-robust face signature for multi-view face recognition. 36. 1–8. 14 indexed citations

9.

Zhang, Lingfeng, Pengfei Dou, Shishir K. Shah, & Ioannis A. Kakadiaris. (2015). Hierarchical multi-label framework for robust face recognition. 4642. 127–134. 2 indexed citations

10.

Dou, Pengfei, et al.. (2014). Benchmarking 3D Pose Estimation for Face Recognition. 2. 190–195. 6 indexed citations

11.

Dou, Pengfei, et al.. (2014). Robust 3D Face Shape Reconstruction from Single Images via Two-Fold Coupled Structure Learning and Off-the-Shelf Landmark Detectors. 131.1–131.13. 8 indexed citations

12.

Xu, Qian, Ruihua Zhang, Linlin Chen, et al.. (2012). Complete Genome Sequence of a Duck Hepatitis A Virus Type 3 Identified in Eastern China. Journal of Virology. 86(24). 13848–13848. 20 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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