Guocan Feng

1.9k total citations
76 papers, 1.3k citations indexed

About

Guocan Feng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Guocan Feng has authored 76 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Computer Vision and Pattern Recognition, 23 papers in Artificial Intelligence and 9 papers in Computational Mechanics. Recurrent topics in Guocan Feng's work include Face and Expression Recognition (31 papers), Image Retrieval and Classification Techniques (13 papers) and Face recognition and analysis (10 papers). Guocan Feng is often cited by papers focused on Face and Expression Recognition (31 papers), Image Retrieval and Classification Techniques (13 papers) and Face recognition and analysis (10 papers). Guocan Feng collaborates with scholars based in China, Hong Kong and United States. Guocan Feng's co-authors include Pong C. Yuen, Jianmin Jiang, Weifu Chen, Y.-F. Liu, Jian Lai, Ling Huang, Jiaxin Cai, Xin Tang, Andrew J. Armstrong and Qianying Wang and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Power Electronics.

In The Last Decade

Guocan Feng

72 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Guocan Feng China	19	886	242	158	143	142	76	1.3k
J. Woodfill United States	15	1.1k 1.3×	177 0.7×	135 0.9×	172 1.2×	158 1.1×	34	1.5k
Jinshi Cui China	18	836 0.9×	349 1.4×	50 0.3×	74 0.5×	78 0.5×	63	1.2k
Hamid Reza Pourreza Iran	21	980 1.1×	237 1.0×	115 0.7×	153 1.1×	53 0.4×	112	1.9k
Thanarat H. Chalidabhongse Thailand	14	1.4k 1.6×	212 0.9×	38 0.2×	163 1.1×	107 0.8×	49	1.6k
Kevin Lai United States	10	1.5k 1.6×	273 1.1×	35 0.2×	102 0.7×	90 0.6×	14	1.8k
Peizhao Zhang United States	14	1.4k 1.6×	825 3.4×	63 0.4×	73 0.5×	146 1.0×	28	1.9k
Alfredo Gardel Spain	20	536 0.6×	142 0.6×	118 0.7×	111 0.8×	66 0.5×	104	1.2k
Chengjun Liu United States	16	763 0.9×	136 0.6×	167 1.1×	160 1.1×	27 0.2×	76	1.0k
Mario E. Munich United States	17	607 0.7×	138 0.6×	122 0.8×	64 0.4×	61 0.4×	38	909
Oleg Naroditsky United States	8	1.9k 2.1×	113 0.5×	190 1.2×	65 0.5×	29 0.2×	11	2.3k

Countries citing papers authored by Guocan Feng

Since Specialization

Citations

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

Fields of papers citing papers by Guocan Feng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guocan Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Guocan Feng. A scholar is included among the top collaborators of Guocan Feng 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 Guocan Feng. Guocan Feng 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:

20 of 20 papers shown

Lu, Yun, et al.. (2025). AAGCN: An adaptive data augmentation for graph contrastive learning. Pattern Recognition. 163. 111471–111471. 2 indexed citations

Fei, Wang, et al.. (2025). Ultra-Short-Term Power Probabilistic Forecasting Method for Distributed Photovoltaic Based on Joint Distribution Modeling. IEEE Transactions on Industry Applications. 62(1). 26–36.

Zou, Na, Mengnan Du, Weifu Chen, et al.. (2024). Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(7). 4625–4640. 9 indexed citations

Chen, Weifu, et al.. (2024). CC-GNN: A Clustering Contrastive Learning Network for Graph Semi-Supervised Learning. IEEE Access. 12. 71956–71969. 4 indexed citations

Deng, Huiqi, Na Zou, Mengnan Du, et al.. (2021). A Unified Taylor Framework for Revisiting Attribution Methods. Proceedings of the AAAI Conference on Artificial Intelligence. 35(13). 11462–11469. 13 indexed citations

Tang, Xin, Guocan Feng, Xiaoxin Li, & Jiaxin Cai. (2015). Learning Low-Rank Class-Specific Dictionary and Sparse Intra-Class Variant Dictionary for Face Recognition. PLoS ONE. 10(11). e0142403–e0142403. 2 indexed citations

Zhang, Yanwen, et al.. (2014). Study on Grinding Force of High Volume Fraction SiCp/Al Composites with Rotary Ultrasonic Vibration Grinding. Advanced materials research. 1027. 48–51. 5 indexed citations

Cai, Jiaxin, Xin Tang, & Guocan Feng. (2014). Learning Pose Dictionary for Human Action Recognition. 54. 381–386. 8 indexed citations

Yuen, Pong C., et al.. (2011). Similarity learning for semi-supervised multi-class boosting. 11. 2164–2167. 2 indexed citations

10.

Chen, Weifu & Guocan Feng. (2010). Semi-supervised Graph Learning: Near Strangers or Distant Relatives. 22. 3368–3371. 2 indexed citations

11.

Cai, Jiaxin, Feng Yang, & Guocan Feng. (2009). Fast Semi-Supervised Fuzzy Clustering: Approach and Application. 1–5.

12.

Feng, Guocan. (2008). Research and Practice on Teaching Methods and Measures of Modern Engineering Graphics. Journal of Donghua University.

13.

Feng, Guocan, et al.. (2008). Kernel Bisecting k-means clustering for SVM training sample reduction. Proceedings - International Conference on Pattern Recognition. 1–4. 8 indexed citations

14.

Feng, Guocan, et al.. (2008). Fruit Detachment and Classification Method for Strawberry Harvesting Robot. International Journal of Advanced Robotic Systems. 5(1). 44 indexed citations

15.

Feng, Guocan, et al.. (2008). intehweb.com Fruit Detachment and Classification Method for Strawberry Harvesting Robot. 1 indexed citations

16.

Jiang, Jianmin, et al.. (2007). Progressive content access to databases of JPEG-compressed images. IET Image Processing. 1(2). 207–214. 2 indexed citations

17.

Feng, Guocan, et al.. (2004). A new current mode fuzzy logic controller with extended state observer for DC-to-DC converters. 3. 1771–1777. 8 indexed citations

18.

Feng, Guocan, et al.. (2004). A new design method for PI-like fuzzy logic controllers for DC-to-DC converters. 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551). 98 h 871. 3751–3757. 23 indexed citations

19.

Feng, Guocan & Jianmin Jiang. (2002). JPEG compressed image retrieval via statistical features. Pattern Recognition. 36(4). 977–985. 58 indexed citations

20.

Yuen, Pong C. & Guocan Feng. (1996). A novel method for parameter estimation of digital arc. Pattern Recognition Letters. 17(9). 929–938. 18 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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