Hanbin Zhao

435 total citations
20 papers, 254 citations indexed

About

Hanbin Zhao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Pollution. According to data from OpenAlex, Hanbin Zhao has authored 20 papers receiving a total of 254 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 2 papers in Pollution. Recurrent topics in Hanbin Zhao's work include Multimodal Machine Learning Applications (10 papers), Domain Adaptation and Few-Shot Learning (10 papers) and Advanced Neural Network Applications (5 papers). Hanbin Zhao is often cited by papers focused on Multimodal Machine Learning Applications (10 papers), Domain Adaptation and Few-Shot Learning (10 papers) and Advanced Neural Network Applications (5 papers). Hanbin Zhao collaborates with scholars based in China, Singapore and Japan. Hanbin Zhao's co-authors include Xi Li, Yongjian Fu, Fei Wu, Hui Wang, Xu Tan, Hui Wang, Qi Tian, Xin Qin, Shiming Ding and Musong Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Hazardous Materials and IEEE Transactions on Image Processing.

In The Last Decade

Hanbin Zhao

16 papers receiving 251 citations

Peers

Hanbin Zhao

CVPR

RNMI

POLLU

Nan Pu China

Aadarsh Jha United States

Peihao Wang United States

Wenqi Shao China

Vladimir Berikov Russia

Dmitry Molchanov Russia

George Cazenavette United States

Chenlin Meng United States

M. Arunkumar India

Edgar Román-Rangel Mexico

Nan Pu China

Hanbin Zhao

175 ×1.0

340 ×2.6

CVPR

8 ×0.4

RNMI

10 ×0.7

4 ×0.3

POLLU

Citations per year, relative to Hanbin Zhao Hanbin Zhao (= 1×) peers Nan Pu

Countries citing papers authored by Hanbin Zhao

Since Specialization

Citations

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

Fields of papers citing papers by Hanbin Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanbin Zhao

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

All Works

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20 of 20 papers shown

Zhao, Hanbin, et al.. (2025). GCSTG: Generating Class-Confusion-Aware Samples With a Tree-Structure Graph for Few-Shot Object Detection. IEEE Transactions on Image Processing. 34. 772–784.

Sun, Hailong, Da-Wei Zhou, Hanbin Zhao, et al.. (2025). MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 39(19). 20699–20707.

Ji, Wei, et al.. (2025). DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous Driving Data Generation. ACM Transactions on Multimedia Computing Communications and Applications. 21(3). 1–29. 2 indexed citations

Li, Mengze, Wei Ji, Jingyuan Chen, et al.. (2024). Hierarchical Debiasing and Noisy Correction for Cross-domain Video Tube Retrieval. 9271–9280. 2 indexed citations

Wang, Hui, et al.. (2024). Unsupervised Domain Adaptation With Class-Aware Memory Alignment. IEEE Transactions on Neural Networks and Learning Systems. 35(7). 9930–9942. 2 indexed citations

Song, Yijun, Hanbin Zhao, Xin Ma, et al.. (2024). Spatiotemporal distribution, mobilization kinetics and risk assessment of nickel in sediments of Lake Taihu, China. Journal of Soils and Sediments. 24(4). 1875–1886. 1 indexed citations

Lui, John C. S., et al.. (2024). D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models. 1725–1749. 1 indexed citations

Wang, Shuhang, et al.. (2023). Seasonal variations in spatial distribution, mobilization kinetic and toxicity risk of arsenic in sediments of Lake Taihu, China. Journal of Hazardous Materials. 463. 132852–132852. 12 indexed citations

Cai, Li, et al.. (2023). The Root Tip of Submerged Plants: An Efficient Engine for Carbon Mineralization. Environmental Science & Technology Letters. 10(4). 385–390. 12 indexed citations

10.

Zhao, Hanbin, et al.. (2022). Epoch-Evolving Gaussian Process Guided Learning for Classification. IEEE Transactions on Neural Networks and Learning Systems. 35(1). 326–337. 3 indexed citations

11.

Zhao, Hanbin, et al.. (2022). Adma-GAN: Attribute-Driven Memory Augmented GANs for Text-to-Image Generation.. Proceedings of the 30th ACM International Conference on Multimedia. 1593–1602. 10 indexed citations

12.

Qin, Xin, et al.. (2022). PcmNet: Position-sensitive context modeling network for temporal action localization. Neurocomputing. 510. 48–58. 13 indexed citations

13.

Wang, Hui, et al.. (2022). Structure-conditioned adversarial learning for unsupervised domain adaptation. Neurocomputing. 497. 216–226. 7 indexed citations

14.

Zhao, Hanbin, et al.. (2021). What and Where: Learn to Plug Adapters via NAS for Multidomain Learning. IEEE Transactions on Neural Networks and Learning Systems. 33(11). 6532–6544. 11 indexed citations

15.

Zhao, Hanbin, Hui Wang, Yongjian Fu, Fei Wu, & Xi Li. (2021). Memory-Efficient Class-Incremental Learning for Image Classification. IEEE Transactions on Neural Networks and Learning Systems. 33(10). 5966–5977. 66 indexed citations

16.

Zhao, Hanbin, et al.. (2021). MgSvF: Multi-Grained Slow versus Fast Framework for Few-Shot Class-Incremental Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(3). 1576–1588. 53 indexed citations

17.

Fu, Yongjian, Songyuan Li, Hanbin Zhao, et al.. (2021). Elastic Knowledge Distillation by Learning From Recollection. IEEE Transactions on Neural Networks and Learning Systems. 34(5). 2647–2658. 5 indexed citations

18.

Zhao, Hanbin, et al.. (2021). When Video Classification Meets Incremental Classes. 880–889. 14 indexed citations

19.

Wang, Hui, et al.. (2018). Progressive Blockwise Knowledge Distillation for Neural Network Acceleration. 2769–2775. 40 indexed citations

20.

Tan, Zhiying, et al.. (2017). An edge feature-based approach for workpiece localization and determination of feasible clamping regions. 5933–5938.

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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