Zhezhou Yu

421 total citations
22 papers, 279 citations indexed

About

Zhezhou Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Zhezhou Yu has authored 22 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 3 papers in Computational Theory and Mathematics. Recurrent topics in Zhezhou Yu's work include Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (8 papers) and Multimodal Machine Learning Applications (4 papers). Zhezhou Yu is often cited by papers focused on Advanced Image and Video Retrieval Techniques (9 papers), Image Retrieval and Classification Techniques (8 papers) and Multimodal Machine Learning Applications (4 papers). Zhezhou Yu collaborates with scholars based in China, Australia and United Kingdom. Zhezhou Yu's co-authors include Shuchao Pang, Mehmet A. Orgun, Jorge Díez, Juan José del Coz, Oscar Luaces, Chunguang Zhou, Libiao Zhang, Bilin Wang, Zhe Zhang and Lan Huang and has published in prestigious journals such as IEEE Access, Computer Methods and Programs in Biomedicine and Engineering Applications of Artificial Intelligence.

In The Last Decade

Zhezhou Yu

20 papers receiving 266 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhezhou Yu China	7	155	94	60	25	22	22	279
Bunil Kumar Balabantaray India	9	116 0.7×	124 1.3×	87 1.4×	29 1.2×	29 1.3×	50	297
Patrick Kwabena Mensah Ghana	7	117 0.8×	119 1.3×	64 1.1×	42 1.7×	14 0.6×	27	371
Ibtissam Bakkouri Morocco	8	115 0.7×	150 1.6×	94 1.6×	45 1.8×	44 2.0×	11	348
Yanhong Luo China	5	129 0.8×	101 1.1×	86 1.4×	21 0.8×	14 0.6×	7	320
M. Ramya India	9	65 0.4×	56 0.6×	61 1.0×	21 0.8×	30 1.4×	51	246
Kwabena Adu Ghana	9	77 0.5×	110 1.2×	77 1.3×	39 1.6×	20 0.9×	24	287
Erdal Özbay Türkiye	12	120 0.8×	132 1.4×	72 1.2×	58 2.3×	34 1.5×	39	344
Yuanming Gao China	4	138 0.9×	109 1.2×	100 1.7×	53 2.1×	44 2.0×	9	276
Hossein Kashiani United States	6	179 1.2×	143 1.5×	103 1.7×	51 2.0×	31 1.4×	16	347

Countries citing papers authored by Zhezhou Yu

Since Specialization

Citations

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

Fields of papers citing papers by Zhezhou Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhezhou Yu

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

Yu, Zhezhou, et al.. (2023). Integrating grid features and geometric coordinates for enhanced image captioning. Applied Intelligence. 54(1). 231–245. 2 indexed citations

Zhang, Zhe, et al.. (2023). Attention Guided Enhancement Network for Weakly Supervised Semantic Segmentation. Chinese Journal of Electronics. 32(4). 896–907. 6 indexed citations

Yu, Zhezhou, et al.. (2021). A Hierarchical Sequence-to-Sequence Model for Korean POS Tagging. ACM Transactions on Asian and Low-Resource Language Information Processing. 20(2). 1–13. 2 indexed citations

Zhang, Zhe, Bilin Wang, Zhezhou Yu, & Zhiyuan Li. (2021). Dilated Convolutional Pixels Affinity Network for Weakly Supervised Semantic Segmentation. Chinese Journal of Electronics. 30(6). 1120–1130. 6 indexed citations

Liu, Hongru, Zhezhou Yu, Xiaowei Xu, et al.. (2021). Global Attention Augmentation Ghost Module: More Features from Lightweight Global Attention Extraction. 5. 40–48. 1 indexed citations

Yu, Zhezhou, et al.. (2020). A Korean named entity recognition method using Bi-LSTM-CRF and masked self-attention. Computer Speech & Language. 65. 101134–101134. 22 indexed citations

Li, Xiaoyue, et al.. (2020). Research on Movie Rating Prediction Algorithms. 12. 121–125. 5 indexed citations

Li, Zhe, et al.. (2019). A Novel Multi-Thread Parallel Constraint Propagation Scheme. IEEE Access. 7. 167823–167835. 1 indexed citations

Pang, Shuchao, et al.. (2018). A novel fused convolutional neural network for biomedical image classification. Medical & Biological Engineering & Computing. 57(1). 107–121. 62 indexed citations

10.

Pang, Shuchao, Mehmet A. Orgun, & Zhezhou Yu. (2018). A novel biomedical image indexing and retrieval system via deep preference learning. Computer Methods and Programs in Biomedicine. 158. 53–69. 24 indexed citations

11.

Pang, Shuchao, Zhezhou Yu, & Mehmet A. Orgun. (2017). A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images. Computer Methods and Programs in Biomedicine. 140. 283–293. 66 indexed citations

12.

Pang, Shuchao, Juan José del Coz, Zhezhou Yu, Oscar Luaces, & Jorge Díez. (2017). Deep learning to frame objects for visual target tracking. Engineering Applications of Artificial Intelligence. 65. 406–420. 43 indexed citations

13.

Pang, Shuchao, Juan José del Coz, Zhezhou Yu, Oscar Luaces, & Jorge Díez. (2017). Deep Learning and Preference Learning for Object Tracking: A Combined Approach. Neural Processing Letters. 47(3). 859–876. 13 indexed citations

14.

Pang, Shuchao, et al.. (2017). Leveraging deep preference learning for indexing and retrieval of biomedical images. 126–129. 1 indexed citations

15.

Liu, Xiangdong, et al.. (2010). Re-weighting relevance feedback image retrieval algorithm based on particle swarm optimization. 2010 Sixth International Conference on Natural Computation. 41. 3609–3613. 4 indexed citations

16.

Zhang, Libiao, et al.. (2009). The application of particle swarm optimization in relevance feedback. 156–159. 1 indexed citations

17.

Zhou, Chunguang, et al.. (2009). A Moving Target Detection Algorithm Based on the Dynamic Background. 1–5. 7 indexed citations

18.

Zhang, Libiao, et al.. (2008). The Application of DWT and SVD in Image Retrieval. 257–261. 5 indexed citations

19.

Zhang, Libiao, et al.. (2008). Image Retrieval Using Multi-granularity Features of Color and Texture. 34. 54–58. 3 indexed citations

20.

Yang, Guohui, et al.. (2004). A method based on improved Bayesian inference network model and hidden Markov model for prediction of protein secondary structure. 2. 134–137.

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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