Yifan Zuo

552 total citations
34 papers, 395 citations indexed

About

Yifan Zuo is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Signal Processing. According to data from OpenAlex, Yifan Zuo has authored 34 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 9 papers in Media Technology and 8 papers in Signal Processing. Recurrent topics in Yifan Zuo's work include Advanced Vision and Imaging (15 papers), Image Enhancement Techniques (15 papers) and Image and Video Quality Assessment (11 papers). Yifan Zuo is often cited by papers focused on Advanced Vision and Imaging (15 papers), Image Enhancement Techniques (15 papers) and Image and Video Quality Assessment (11 papers). Yifan Zuo collaborates with scholars based in China, Australia and Canada. Yifan Zuo's co-authors include Yuming Fang, Ping An, Qiang Wu, Jian Zhang, Yong Yang, Xiwu Shang, Shuying Huang, Wenying Wen, Jiancheng Sun and Leida Li and has published in prestigious journals such as Food Chemistry, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Yifan Zuo

29 papers receiving 391 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yifan Zuo China	10	358	226	30	30	26	34	395
Praful Gupta United States	8	418 1.2×	193 0.9×	20 0.7×	43 1.4×	12 0.5×	15	469
YiChang Shih United States	9	613 1.7×	137 0.6×	24 0.8×	11 0.4×	21 0.8×	13	663
Seo-Won Ji South Korea	6	447 1.2×	221 1.0×	11 0.4×	7 0.2×	20 0.8×	12	502
Huixuan Tang Canada	7	334 0.9×	235 1.0×	22 0.7×	7 0.2×	13 0.5×	10	362
Zhongfu Ye China	6	295 0.8×	127 0.6×	33 1.1×	56 1.9×	10 0.4×	11	369
Abdelrahman Abdelhamed Canada	5	481 1.3×	291 1.3×	14 0.5×	7 0.2×	11 0.4×	10	509
Mikaël Le Pendu France	9	292 0.8×	54 0.2×	14 0.5×	38 1.3×	9 0.3×	20	321
Hai Jiang China	8	369 1.0×	136 0.6×	19 0.6×	4 0.1×	30 1.2×	12	403
Sunil Jaiswal India	10	251 0.7×	104 0.5×	13 0.4×	10 0.3×	23 0.9×	35	293
Pradip Paudyal Italy	11	304 0.8×	109 0.5×	39 1.3×	43 1.4×	13 0.5×	16	336

Countries citing papers authored by Yifan Zuo

Since Specialization

Citations

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

Fields of papers citing papers by Yifan Zuo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yifan Zuo

This figure shows the co-authorship network connecting the top 25 collaborators of Yifan Zuo. A scholar is included among the top collaborators of Yifan Zuo 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 Yifan Zuo. Yifan Zuo 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

Chen, Yurong, Jing Wang, Yifan Zuo, et al.. (2025). Improvement of near-infrared spectroscopic assessment methods for the quality of Keemun black tea: Utilizing transfer learning. Food Research International. 209. 116184–116184.

Zuo, Yifan, et al.. (2025). Exploring the colorimetric sensing mechanism of metal porphyrin on the degree of roasting from the perspective of density functional theory. Food Chemistry. 477. 143330–143330. 1 indexed citations

Wang, Wenya, et al.. (2025). LED spectral tailoring directs flavor metabolites during white tea withering. LWT. 231. 118316–118316.

Ding, Keyan, et al.. (2024). CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement. International Journal of Computer Vision. 132(12). 5983–6003. 6 indexed citations

Li, Zhen, Dandan Wang, Yuze Mao, et al.. (2024). Design and verification of a novel self-powered sensing system for intelligent bearings. Measurement Science and Technology. 36(1). 15132–15132.

Shang, Xiwu, et al.. (2023). Fast CU size decision algorithm for VVC intra coding. Multimedia Tools and Applications. 82(18). 28301–28322. 9 indexed citations

Zuo, Yifan, Yuming Fang, & Kede Ma. (2023). The critical review of the growth of deep learning-based image fusion techniques. Journal of Image and Graphics. 28(1). 102–117. 1 indexed citations

Shang, Xiwu, et al.. (2021). Color-Sensitivity-Based Rate-Distortion Optimization for H.265/HEVC. IEEE Transactions on Circuits and Systems for Video Technology. 32(2). 802–812. 4 indexed citations

Shang, Xiwu, et al.. (2019). A Novel Objective Quality Assessment Method for Transcoded Videos From H.264/AVC to H.265/HEVC Utilizing Probability Theory. IEEE Transactions on Broadcasting. 65(4). 777–781. 5 indexed citations

10.

Zuo, Yifan, Qiang Wu, Yuming Fang, et al.. (2019). Multi-Scale Frequency Reconstruction for Guided Depth Map Super-Resolution via Deep Residual Network. IEEE Transactions on Circuits and Systems for Video Technology. 30(2). 297–306. 59 indexed citations

11.

Zuo, Yifan, et al.. (2019). Residual dense network for intensity-guided depth map enhancement. Information Sciences. 495. 52–64. 25 indexed citations

12.

Shang, Xiwu, et al.. (2019). Weighting Quantization Matrices for HEVC/H.265-Coded RGB Videos. IEEE Access. 7. 36019–36032. 5 indexed citations

13.

Fang, Yuming, et al.. (2019). Perceptual Quality Assessment for Screen Content Images by Spatial Continuity. IEEE Transactions on Circuits and Systems for Video Technology. 30(11). 4050–4063. 37 indexed citations

14.

Zuo, Yifan, Qiang Wu, Jian Zhang, & Ping An. (2018). Minimum Spanning Forest With Embedded Edge Inconsistency Measurement Model for Guided Depth Map Enhancement. IEEE Transactions on Image Processing. 27(8). 4145–4159. 21 indexed citations

15.

Zuo, Yifan, Qiang Wu, Jian Zhang, & Ping An. (2017). Minimum spanning forest with embedded edge inconsistency measurement for color-guided depth map upsampling. 26. 211–216. 7 indexed citations

16.

Zuo, Yifan, Qiang Wu, Jian Zhang, & Ping An. (2016). Explicit Edge Inconsistency Evaluation Model for Color-Guided Depth Map Enhancement. IEEE Transactions on Circuits and Systems for Video Technology. 28(2). 439–453. 40 indexed citations

17.

Zuo, Yifan, Qiang Wu, Jian Zhang, & Ping An. (2016). Explicit modeling on depth-color inconsistency for color-guided depth up-sampling. 26. 1–6. 11 indexed citations

18.

Zuo, Yifan, Qiang Wu, Ping An, & Jian Zhang. (2016). Explicit measurement on depth-color inconsistency for depth completion. 26. 4037–4041. 1 indexed citations

19.

Wang, Jianxin, et al.. (2014). High accuracy hole filling for Kinect depth maps. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9273. 92732L–92732L. 5 indexed citations

20.

Li, Hejian, et al.. (2011). Depth estimation system suitable for hardware design. Journal of Shanghai University (English Edition). 15(4). 325–330. 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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