Tingjin Luo

516 total citations
39 papers, 365 citations indexed

About

Tingjin Luo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Tingjin Luo has authored 39 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 21 papers in Artificial Intelligence and 5 papers in Computational Mechanics. Recurrent topics in Tingjin Luo's work include Face and Expression Recognition (14 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Text and Document Classification Technologies (8 papers). Tingjin Luo is often cited by papers focused on Face and Expression Recognition (14 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Text and Document Classification Technologies (8 papers). Tingjin Luo collaborates with scholars based in China, United States and Singapore. Tingjin Luo's co-authors include Chenping Hou, Dongyun Yi, Feiping Nie, Hong Tao, Ruidong Fan, Zhi‐Hua Zhou, Yuanyuan Jiao, Hao Zhou, Jun Zhang and Jieping Ye and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Tingjin Luo

33 papers receiving 357 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tingjin Luo China 12 248 176 66 45 23 39 365
Jidong Zhao China 9 312 1.3× 243 1.4× 49 0.7× 31 0.7× 35 1.5× 17 442
Yuanyuan Jiao China 8 232 0.9× 144 0.8× 73 1.1× 68 1.5× 28 1.2× 22 343
Lai Tian China 10 346 1.4× 249 1.4× 86 1.3× 50 1.1× 28 1.2× 14 469
Lele Fu China 10 290 1.2× 271 1.5× 45 0.7× 43 1.0× 10 0.4× 27 464
Litao Yu Australia 8 262 1.1× 174 1.0× 38 0.6× 16 0.4× 20 0.9× 27 399
Haifeng Zhao China 8 242 1.0× 119 0.7× 58 0.9× 54 1.2× 12 0.5× 35 344
Danyang Wu China 14 404 1.6× 365 2.1× 88 1.3× 46 1.0× 29 1.3× 43 607
Changqing Zhang China 11 236 1.0× 231 1.3× 50 0.8× 18 0.4× 24 1.0× 21 420
Bac Nguyen Belgium 9 188 0.8× 159 0.9× 20 0.3× 26 0.6× 10 0.4× 12 320

Countries citing papers authored by Tingjin Luo

Since Specialization
Citations

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

Fields of papers citing papers by Tingjin Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingjin Luo

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

All Works

20 of 20 papers shown
1.
Lu, Jun, Tingjin Luo, & Kai Li. (2025). A forward k-means algorithm for regression clustering. Information Sciences. 711. 122105–122105. 1 indexed citations
2.
Zhou, Tongxue, Su Ruan, Tingjin Luo, et al.. (2025). A reliable framework for brain tumor segmentation via multi-modal fusion and uncertainty modeling. Information Fusion. 129. 104085–104085.
3.
4.
Huang, Yu‐An, et al.. (2025). Noise-free prototype guided representation calibration under label noise. Knowledge-Based Systems. 329. 114308–114308.
5.
Luo, Tingjin, et al.. (2025). Semi-Supervised Multi-View Multi-Label Learning with View-Specific Transformer and Enhanced Pseudo-Label. Proceedings of the AAAI Conference on Artificial Intelligence. 39(17). 18430–18438.
6.
Luo, Tingjin, et al.. (2025). Exploring the Essence of Relationships for Scene Graph Generation via Causal Features Enhancement Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(8). 6616–6630. 1 indexed citations
7.
Luo, Tingjin, et al.. (2024). Dynamic collaborative learning with heterogeneous knowledge transfer for long-tailed visual recognition. Information Fusion. 115. 102734–102734. 3 indexed citations
8.
Luo, Tingjin, et al.. (2024). Deep Incomplete Multi-View Network Semi-Supervised Multi-Label Learning with Unbiased Loss. 9048–9056. 5 indexed citations
9.
Luo, Tingjin, et al.. (2024). Deep Incomplete Multi-View Learning Network with Insufficient Label Information. Proceedings of the AAAI Conference on Artificial Intelligence. 38(11). 12919–12927. 6 indexed citations
10.
Tao, Hong, et al.. (2024). Compound Weakly Supervised Clustering. IEEE Transactions on Image Processing. 33. 957–971. 2 indexed citations
11.
12.
Luo, Tingjin, et al.. (2023). Decorrelated spectral regression: An unsupervised dimension reduction method under data selection bias. Neurocomputing. 549. 126406–126406. 4 indexed citations
13.
Zhou, Hao, Jun Zhang, Tingjin Luo, Yazhou Yang, & Jun Lei. (2022). Debiased Scene Graph Generation for Dual Imbalance Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1–15. 7 indexed citations
14.
Luo, Tingjin, et al.. (2021). Semi-Supervised Learning With Label Proportion. IEEE Transactions on Knowledge and Data Engineering. 35(1). 877–890. 7 indexed citations
15.
Fan, Ruidong, et al.. (2020). Multi-view subspace learning via bidirectional sparsity. Pattern Recognition. 108. 107524–107524. 36 indexed citations
16.
Wang, Haotian, Wenjing Yang, Zhenyu Zhao, et al.. (2019). Rademacher dropout: An adaptive dropout for deep neural network via optimizing generalization gap. Neurocomputing. 357. 177–187. 20 indexed citations
17.
Lin, Zhipeng, et al.. (2019). Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation. 1468–1473. 2 indexed citations
18.
Luo, Tingjin, Chenping Hou, Feiping Nie, & Dongyun Yi. (2018). Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis. IEEE Transactions on Cybernetics. 49(3). 933–946. 36 indexed citations
19.
Yang, Yang, Tingjin Luo, Zhoujun Li, Xiaoming Zhang, & Philip S. Yu. (2017). A Robust Method for Inferring Network Structures. Scientific Reports. 7(1). 5221–5221. 7 indexed citations
20.
Luo, Tingjin, Weizhong Zhang, Shuang Qiu, et al.. (2017). Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 345–354. 11 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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