Jie Hu

1.8k total citations
99 papers, 1.2k citations indexed

About

Jie Hu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Jie Hu has authored 99 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 39 papers in Computer Vision and Pattern Recognition and 14 papers in Computational Theory and Mathematics. Recurrent topics in Jie Hu's work include Face and Expression Recognition (15 papers), Topic Modeling (14 papers) and Rough Sets and Fuzzy Logic (13 papers). Jie Hu is often cited by papers focused on Face and Expression Recognition (15 papers), Topic Modeling (14 papers) and Rough Sets and Fuzzy Logic (13 papers). Jie Hu collaborates with scholars based in China, United States and Japan. Jie Hu's co-authors include Tianrui Li, Bassoma Diallo, Ghufran Ahmad Khan, Mingwei Tang, Hongjun Wang, Hamido Fujita, Chuan Luo, Wen Song, Shengdong Du and Yan Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Jie Hu

91 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
Jie Hu China	21	520	518	218	185	109	99	1.2k
Guolong Chen China	24	534 1.0×	255 0.5×	97 0.4×	320 1.7×	59 0.5×	119	1.9k
Hamed Shah‐Hosseini Iran	13	661 1.3×	337 0.7×	239 1.1×	106 0.6×	76 0.7×	30	1.3k
Shuyin Xia China	24	1.2k 2.2×	658 1.3×	584 2.7×	332 1.8×	141 1.3×	107	1.8k
Jilian Zhang China	17	794 1.5×	333 0.6×	79 0.4×	268 1.4×	114 1.0×	42	1.2k
Yangdong Ye China	23	981 1.9×	955 1.8×	49 0.2×	326 1.8×	67 0.6×	126	1.7k
Harish Sharma India	17	717 1.4×	342 0.7×	256 1.2×	83 0.4×	71 0.7×	53	1.4k
Emrah Hançer Türkiye	19	1.2k 2.4×	499 1.0×	387 1.8×	116 0.6×	71 0.7×	49	1.8k
Katsuhiro Honda Japan	16	816 1.6×	466 0.9×	129 0.6×	212 1.1×	245 2.2×	209	1.3k
Jiangjiang Zhang China	11	385 0.7×	144 0.3×	183 0.8×	221 1.2×	71 0.7×	30	1.0k
Junfeng Yao China	18	311 0.6×	306 0.6×	165 0.8×	76 0.4×	38 0.3×	111	1.2k

Countries citing papers authored by Jie Hu

Since Specialization

Citations

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

Fields of papers citing papers by Jie Hu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jie Hu

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

Hu, Jie, Lei Wang, Bo Peng, Fei Teng, & Tianrui Li. (2025). Efficient fire and smoke detection in complex environments via adaptive spatial feature fusion and dual attention mechanism. Digital Signal Processing. 159. 104982–104982. 3 indexed citations

Tang, Mingwei, et al.. (2024). Dual-enhanced generative model with graph attention network and contrastive learning for aspect sentiment triplet extraction. Knowledge-Based Systems. 301. 112342–112342. 9 indexed citations

Hu, Jie, Chenghao Yang, Kai Huang, et al.. (2024). Information bottleneck fusion for deep multi-view clustering. Knowledge-Based Systems. 289. 111551–111551. 2 indexed citations

Hu, Jie, Yinglian Zhu, Fei Teng, & Tianrui Li. (2024). Temporal knowledge graph reasoning based on relation graphs and time-guided attention mechanism. Knowledge-Based Systems. 301. 112280–112280. 3 indexed citations

Zhang, Jiafan, Bo Peng, Xi Wu, & Jie Hu. (2024). Weakly supervised semantic segmentation by knowledge graph inference. Engineering Applications of Artificial Intelligence. 138. 109294–109294. 3 indexed citations

Tang, Mingwei, et al.. (2024). INA-Net: An integrated noise-adaptive attention neural network for enhanced medical image segmentation. Expert Systems with Applications. 258. 125078–125078. 4 indexed citations

Hu, Jie, et al.. (2024). A knowledge graph completion model based on triple level interaction and contrastive learning. Pattern Recognition. 156. 110783–110783. 7 indexed citations

Diallo, Bassoma, Jie Hu, Tianrui Li, et al.. (2023). Auto-attention mechanism for multi-view deep embedding clustering. Pattern Recognition. 143. 109764–109764. 34 indexed citations

Hu, Jie, et al.. (2023). A contrastive learning based universal representation for time series forecasting. Information Sciences. 635. 86–98. 12 indexed citations

10.

Hu, Jie, et al.. (2023). Text semantic matching with an enhanced sample building method based on contrastive learning. International Journal of Machine Learning and Cybernetics. 14(9). 3105–3112. 3 indexed citations

11.

Khan, Ghufran Ahmad, Jie Hu, Tianrui Li, Bassoma Diallo, & Hongjun Wang. (2023). Multi-view clustering for multiple manifold learning via concept factorization. Digital Signal Processing. 140. 104118–104118. 22 indexed citations

12.

Hu, Jie, et al.. (2023). Multi-view subspace clustering for learning joint representation via low-rank sparse representation. Applied Intelligence. 53(19). 22511–22530. 26 indexed citations

13.

Tang, Mingwei, et al.. (2023). A vulnerability detection algorithm based on residual graph attention networks for source code imbalance (RGAN). Expert Systems with Applications. 238. 122216–122216. 11 indexed citations

14.

Hu, Jie, et al.. (2022). An effective multi-task learning model for end-to-end emotion-cause pair extraction. Applied Intelligence. 53(3). 3519–3529. 8 indexed citations

15.

Hu, Jie, et al.. (2022). Deep linear graph attention model for attributed graph clustering. Knowledge-Based Systems. 246. 108665–108665. 19 indexed citations

16.

Diallo, Bassoma, et al.. (2021). Multi-view document clustering based on geometrical similarity measurement. International Journal of Machine Learning and Cybernetics. 13(3). 663–675. 20 indexed citations

17.

Hu, Jie, et al.. (2021). Multi-view clustering via deep concept factorization. Knowledge-Based Systems. 217. 106807–106807. 63 indexed citations

18.

Khan, Ghufran Ahmad, Jie Hu, Tianrui Li, Bassoma Diallo, & Hongjun Wang. (2021). Multi-view data clustering via non-negative matrix factorization with manifold regularization. International Journal of Machine Learning and Cybernetics. 13(3). 677–689. 59 indexed citations

19.

Li, Tianrui, et al.. (2019). A novel approach for efficient updating approximations in dynamic ordered information systems. Information Sciences. 507. 197–219. 24 indexed citations

20.

Hu, Jie, Tianrui Li, Chuan Luo, Hamido Fujita, & Shaoyong Li. (2016). Incremental fuzzy probabilistic rough sets over two universes. International Journal of Approximate Reasoning. 81. 28–48. 35 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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