Dongbao Yang

1.5k total citations · 1 hit paper
18 papers, 904 citations indexed

About

Dongbao Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Dongbao Yang has authored 18 papers receiving a total of 904 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 2 papers in Information Systems. Recurrent topics in Dongbao Yang's work include Handwritten Text Recognition Techniques (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (5 papers). Dongbao Yang is often cited by papers focused on Handwritten Text Recognition Techniques (7 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (5 papers). Dongbao Yang collaborates with scholars based in China and Canada. Dongbao Yang's co-authors include Hongtao Xie, Yongdong Zhang, Zhineng Chen, Nannan Sun, Yu Zhou, Weiping Wang, Jian Yin, Chenggang Yan, Qionghai Dai and Zhi Qiao and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Intelligent Transportation Systems and IEEE Signal Processing Letters.

In The Last Decade

Dongbao Yang

16 papers receiving 884 citations

Hit Papers

Automated pulmonary nodule detection in CT images using d... 2018 2026 2020 2023 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Automated pulmonary nodule detection in CT images using deep convolutional neural networks
    2018 330 citations Hongtao Xie, Dongbao Yang et al. Pattern Recognition profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dongbao Yang China 7 522 301 276 194 83 18 904
S.A. Karkanis Greece 14 499 1.0× 263 0.9× 188 0.7× 145 0.7× 79 1.0× 40 987
Xiabi Liu China 15 449 0.9× 370 1.2× 383 1.4× 140 0.7× 110 1.3× 72 893
Yongyi Yang United States 4 451 0.9× 648 2.2× 360 1.3× 104 0.5× 79 1.0× 6 976
Hyeonseob Nam South Korea 6 590 1.1× 649 2.2× 281 1.0× 84 0.4× 47 0.6× 9 1.1k
Bisser Raytchev Japan 13 367 0.7× 169 0.6× 202 0.7× 295 1.5× 40 0.5× 78 922
D. Brzaković United States 13 407 0.8× 382 1.3× 294 1.1× 233 1.2× 87 1.0× 50 804
Xiaoqing Guo Hong Kong 15 535 1.0× 394 1.3× 232 0.8× 38 0.2× 61 0.7× 33 833
S. S. Kumar India 17 357 0.7× 321 1.1× 343 1.2× 166 0.9× 77 0.9× 82 922
Jyh-Shyan Lin United States 9 297 0.6× 374 1.2× 380 1.4× 193 1.0× 47 0.6× 25 823

Countries citing papers authored by Dongbao Yang

Since Specialization
Citations

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

Fields of papers citing papers by Dongbao Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongbao Yang

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

All Works

18 of 18 papers shown
1.
Yang, Dongbao, et al.. (2025). Specifying What You Know or Not for Multi-Label Class-Incremental Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 39(21). 22345–22353.
2.
Wang, Wei, et al.. (2025). Arbitrary Reading Order Scene Text Spotter with Local Semantics Guidance. Proceedings of the AAAI Conference on Artificial Intelligence. 39(6). 5919–5927. 3 indexed citations
3.
4.
Qiao, Zhi, et al.. (2024). Masked and Permuted Implicit Context Learning for Scene Text Recognition. IEEE Signal Processing Letters. 31. 964–968. 4 indexed citations
5.
Yang, Dongbao, et al.. (2024). Accurate and Robust Scene Text Recognition via Adversarial Training. 4275–4279. 1 indexed citations
6.
Yang, Dongbao, et al.. (2023). Pseudo Object Replay and Mining for Incremental Object Detection. 153–162. 2 indexed citations
7.
8.
Yang, Dongbao, et al.. (2023). One-Shot Replay: Boosting Incremental Object Detection via Retrospecting One Object. Proceedings of the AAAI Conference on Artificial Intelligence. 37(3). 3127–3135. 5 indexed citations
9.
Yang, Xinye, et al.. (2023). Mask-Guided Stamp Erasure for Real Document Image. 1631–1636. 2 indexed citations
10.
Yang, Dongbao, et al.. (2022). Multi-View correlation distillation for incremental object detection. Pattern Recognition. 131. 108863–108863. 44 indexed citations
11.
Yang, Dongbao, Yu Zhou, Wei Shi, Dayan Wu, & Weiping Wang. (2022). RD-IOD: Two-Level Residual-Distillation-Based Triple-Network for Incremental Object Detection. ACM Transactions on Multimedia Computing Communications and Applications. 18(1). 1–23. 16 indexed citations
12.
Wang, Wei, et al.. (2021). Self-Training for Domain Adaptive Scene Text Detection. 850–857. 13 indexed citations
13.
Luo, Dezhao, Chang Liu, Yu Zhou, et al.. (2020). Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 34(7). 11701–11708. 99 indexed citations
14.
Qiao, Zhi, Yu Zhou, Dongbao Yang, Yucan Zhou, & Weiping Wang. (2020). SEED: Semantics Enhanced Encoder-Decoder Framework for Scene Text Recognition. 13525–13534. 164 indexed citations
15.
Xie, Hongtao, Dongbao Yang, Nannan Sun, Zhineng Chen, & Yongdong Zhang. (2018). Automated pulmonary nodule detection in CT images using deep convolutional neural networks. Pattern Recognition. 85. 109–119. 330 indexed citations breakdown →
16.
Yang, Dongbao, et al.. (2017). Supervised deep quantization for efficient image search. 42. 525–530. 2 indexed citations
17.
Yan, Chenggang, Hongtao Xie, Dongbao Yang, et al.. (2017). Supervised Hash Coding With Deep Neural Network for Environment Perception of Intelligent Vehicles. IEEE Transactions on Intelligent Transportation Systems. 19(1). 284–295. 210 indexed citations
18.
Chen, Lihong, et al.. (2011). The research of rainfall prediction models based on Matlab neural network. 19. 45–48. 6 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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