Zhenbing Liu

2.8k total citations · 1 hit paper
101 papers, 1.8k citations indexed

About

Zhenbing Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Zhenbing Liu has authored 101 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Vision and Pattern Recognition, 32 papers in Artificial Intelligence and 27 papers in Media Technology. Recurrent topics in Zhenbing Liu's work include AI in cancer detection (22 papers), Radiomics and Machine Learning in Medical Imaging (19 papers) and Advanced Image Fusion Techniques (17 papers). Zhenbing Liu is often cited by papers focused on AI in cancer detection (22 papers), Radiomics and Machine Learning in Medical Imaging (19 papers) and Advanced Image Fusion Techniques (17 papers). Zhenbing Liu collaborates with scholars based in China, Japan and Australia. Zhenbing Liu's co-authors include Rushi Lan, Xiaonan Luo, Xipeng Pan, Long Sun, Cheng Pang, Huimin Lu, Huihua Yang, Lingqiao Li, Aijun Zhu and Zhi Li and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Expert Systems with Applications and IEEE Access.

In The Last Decade

Zhenbing Liu

87 papers receiving 1.8k citations

Hit Papers

align trajectories

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.

MADNet: A Fast and Lightweight Network for Single-Image Super Resolution

2020 246 citations Rushi Lan, Zhenbing Liu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhenbing Liu China	24	961	688	413	300	195	101	1.8k
Jakub Nalepa Poland	24	849 0.9×	664 1.0×	565 1.4×	200 0.7×	174 0.9×	120	2.2k
Syamsiah Mashohor Malaysia	22	1.0k 1.1×	623 0.9×	283 0.7×	718 2.4×	300 1.5×	96	1.9k
Shengwei Tian China	22	728 0.8×	646 0.9×	177 0.4×	240 0.8×	126 0.6×	137	2.0k
Michał Kawulok Poland	21	924 1.0×	465 0.7×	405 1.0×	164 0.5×	146 0.7×	91	1.9k
Manoj Diwakar India	25	1.2k 1.2×	453 0.7×	590 1.4×	426 1.4×	161 0.8×	217	2.5k
Long Yu China	20	554 0.6×	603 0.9×	166 0.4×	234 0.8×	110 0.6×	153	1.7k
Muwei Jian China	29	1.8k 1.8×	392 0.6×	412 1.0×	255 0.8×	95 0.5×	137	2.6k
Alper Baştürk Türkiye	22	531 0.6×	602 0.9×	151 0.4×	308 1.0×	75 0.4×	58	1.5k
Yi Ding China	24	1.1k 1.1×	497 0.7×	229 0.6×	443 1.5×	484 2.5×	125	2.0k
Ekta Walia India	19	1.3k 1.3×	726 1.1×	287 0.7×	716 2.4×	80 0.4×	55	2.3k

Countries citing papers authored by Zhenbing Liu

Since Specialization

Citations

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

Fields of papers citing papers by Zhenbing Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhenbing Liu

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

Liu, Zhenbing, et al.. (2025). Addressing bayes imbalance in partial label learning via range adaptive graph guided disambiguation. Neurocomputing. 627. 129606–129606.

Lin, Huan, Yumeng Wang, Lingqiao Li, et al.. (2025). Federated cross-source learning for lung nodule segmentation with data characteristic-aware weight optimization. Pattern Recognition. 172. 112396–112396.

Feng, Siyang, Liting Shi, Zhenbing Liu, et al.. (2025). Wave-aware Weakly Supervised Histopathological Tissue Segmentation with Cross-scale Logits Distillation. IEEE Transactions on Medical Imaging. PP. 1–1.

Feng, Siyang, Yanfen Cui, Lingqiao Li, et al.. (2025). Multi-layer Feature Fusion and Coarse-to-fine Label Learning for Semi-supervised Lesion Segmentation of Lung Cancer. Knowledge-Based Systems. 317. 113451–113451. 1 indexed citations

Li, Weixing, Zhen Zhang, Guangyao Wu, et al.. (2025). Data-efficient federated semi-supervised learning framework via pseudo supervision refinement strategy for lung tumor segmentation. Biomedical Signal Processing and Control. 107. 107793–107793.

Zhou, Nan, Siyang Feng, Zhenbing Liu, et al.. (2025). Uncertainty-guided cross teaching semi-supervised framework for histopathology image segmentation with curriculum self-training. Applied Soft Computing. 180. 113328–113328.

Liu, Zhenbing, Yanfen Cui, Xipeng Pan, et al.. (2025). Label-efficient transformer-based framework with self-supervised strategies for heterogeneous lung tumor segmentation. Expert Systems with Applications. 269. 126364–126364. 1 indexed citations

Wu, Wenzhen, et al.. (2024). Steel Surface Defect Detection Based on Denoising Diffusion Implicit Models with Data Augmentation. 15–19. 1 indexed citations

Pan, Xipeng, Rushi Lan, Cheng Lu, et al.. (2023). SMILE: Cost-sensitive multi-task learning for nuclear segmentation and classification with imbalanced annotations. Medical Image Analysis. 88. 102867–102867. 37 indexed citations

10.

Wang, Xiaolong, et al.. (2023). DPACFuse: Dual-Branch Progressive Learning for Infrared and Visible Image Fusion with Complementary Self-Attention and Convolution. Sensors. 23(16). 7205–7205. 3 indexed citations

11.

Lan, Rushi, et al.. (2023). AcFusion: Infrared and Visible Image Fusion Based on Self-Attention and Convolution With Enhanced Information Extraction. IEEE Transactions on Consumer Electronics. 70(1). 4155–4167. 5 indexed citations

12.

Liu, Zhenbing, et al.. (2023). Brighten up Images via Dual-Branch Structure-Texture Awareness Feature Interaction. IEEE Signal Processing Letters. 31. 46–50. 3 indexed citations

13.

Lan, Rushi, et al.. (2023). Single Traffic Image Deraining via Similarity-Diversity Model. IEEE Transactions on Intelligent Transportation Systems. 25(1). 90–103. 3 indexed citations

14.

Liu, Zhenbing, et al.. (2023). Adapting Single-Image Super-Resolution Models to Video Super-Resolution: A Plug-and-Play Approach. Sensors. 23(11). 5030–5030. 1 indexed citations

15.

Liu, Zhenbing, et al.. (2023). Shadow Hunter: Low-Illumination Object-Detection Algorithm. Applied Sciences. 13(16). 9261–9261. 5 indexed citations

16.

Lin, Huan, Zaiyi Liu, Li‐Xu Yan, et al.. (2023). Artificial intelligence-quantified tumour-lymphocyte spatial interaction predicts disease-free survival in resected lung adenocarcinoma: A graph-based, multicentre study. Computer Methods and Programs in Biomedicine. 238. 107617–107617. 4 indexed citations

17.

Liu, Zhenbing, et al.. (2023). Real-Time Video Super-Resolution with Spatio-Temporal Modeling and Redundancy-Aware Inference. Sensors. 23(18). 7880–7880. 3 indexed citations

18.

Wang, Huadeng, Guang Xu, Xipeng Pan, et al.. (2022). Multi-task generative adversarial learning for nuclei segmentation with dual attention and recurrent convolution. Biomedical Signal Processing and Control. 75. 103558–103558. 20 indexed citations

19.

Pan, Xipeng, et al.. (2021). Mitosis detection techniques in H&E stained breast cancer pathological images: A comprehensive review. Computers & Electrical Engineering. 91. 107038–107038. 28 indexed citations

20.

Ma, Chao, Zhenbing Liu, Zhiguang Cao, et al.. (2020). Cost-sensitive deep forest for price prediction. Pattern Recognition. 107. 107499–107499. 45 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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