Renchu Guan

2.7k total citations · 1 hit paper
104 papers, 1.8k citations indexed

About

Renchu Guan is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Renchu Guan has authored 104 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 38 papers in Molecular Biology and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Renchu Guan's work include Topic Modeling (18 papers), Remote-Sensing Image Classification (13 papers) and Text and Document Classification Technologies (13 papers). Renchu Guan is often cited by papers focused on Topic Modeling (18 papers), Remote-Sensing Image Classification (13 papers) and Text and Document Classification Technologies (13 papers). Renchu Guan collaborates with scholars based in China, Italy and United States. Renchu Guan's co-authors include Yanchun Liang, Xiaoyue Feng, Chen Yang, Dong Xu, Lorenzo Bruzzone, Xiaohu Shi, Donghui Wang, Laijun Lu, Fausto Giunchiglia and Zhili Pei and has published in prestigious journals such as Nature Communications, PLoS ONE and Nature Methods.

In The Last Decade

Renchu Guan

92 papers receiving 1.7k 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.

A content-based recommender system for computer science publications

2018 255 citations Yanchun Liang, Dong Xu et al. profile →

Peers

Renchu Guan

AI

CVPR

IS

MT

MB

Carlos J. Alonso Spain

Xiao‐Zhu Xie China

Weixin Xie China

Ji Feng China

Bing Liu China

Fanzhang Li China

Lichuan Gu China

Chieh-Jen Wang Taiwan

Changjing Shang United Kingdom

Carlos J. Alonso Spain

Renchu Guan

911 ×1.1

AI

369 ×1.0

CVPR

178 ×0.6

IS

139 ×0.5

MT

229 ×0.9

MB

Citations per year, relative to Renchu Guan Renchu Guan (= 1×) peers Carlos J. Alonso

Countries citing papers authored by Renchu Guan

Since Specialization

Citations

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

Fields of papers citing papers by Renchu Guan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Renchu Guan

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

1.

Yang, Chen, et al.. (2025). Cross-Modality Adaptive Feature Fusion for Multitype and Multiscale Impact Craters Identification on Mars. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–13. 1 indexed citations

2.

Wang, Zhikang, Liang Chen, Zhi Li, et al.. (2025). High-parameter spatial multi-omics through histology-anchored integration. Nature Methods. 23(2). 373–386.

3.

Fan, Lei, Qingming Tang, Yutong Wang, et al.. (2025). Injury-induced Clusterin+ cardiomyocytes suppress inflammation and promote regeneration in neonatal and adult hearts by reprogramming macrophages. Cell stem cell. 32(12). 1849–1868.e15.

4.

Guo, Fei, Renchu Guan, Yaohang Li, et al.. (2025). Foundation models in bioinformatics. National Science Review. 12(4). nwaf028–nwaf028. 18 indexed citations

5.

Yang, Chen, et al.. (2025). A Semi-Supervised Multi-Scale Convolutional Neural Network for Hyperspectral Image Classification with Limited Labeled Samples. Remote Sensing. 17(19). 3273–3273.

6.

Wang, Yan, et al.. (2024). Multi-Omics Profiling Unveils the Complexity and Dynamics of Immune Infiltrates in Intrahepatic Cholangiocarcinoma. Biology. 13(10). 816–816. 2 indexed citations

7.

Wang, Xinfei, Lan Huang, Yan Wang, et al.. (2024). A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers. Briefings in Bioinformatics. 25(6). 5 indexed citations

8.

Li, Ximing, Lan Huang, Fausto Giunchiglia, et al.. (2024). Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training. ACM Transactions on Knowledge Discovery from Data. 18(9). 1–30.

9.

Wang, Bing, Shengsheng Wang, Changchun Li, Renchu Guan, & Ximing Li. (2024). Harmfully Manipulated Images Matter in Multimodal Misinformation Detection. 2262–2271.

10.

Guan, Renchu, et al.. (2023). Lightweight Attention Network for Very High-Resolution Image Semantic Segmentation. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–14. 18 indexed citations

11.

Yang, Chen, Lorenzo Bruzzone, Bin Liu, et al.. (2023). Comprehensive mapping of lunar surface chemistry by adding Chang'e-5 samples with deep learning. Nature Communications. 14(1). 7554–7554. 27 indexed citations

12.

Li, Ximing, et al.. (2023). Variational Wasserstein Barycenters with C-cyclical Monotonicity Regularization. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7157–7165. 1 indexed citations

13.

Bruzzone, Lorenzo, et al.. (2021). Spectral-Spatial Genetic Algorithm-Based Unsupervised Band Selection for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 59(11). 9616–9632. 37 indexed citations

14.

Zhou, Fengfeng, et al.. (2021). Superpixel-Level Global and Local Similarity Graph-Based Clustering for Large Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–16. 20 indexed citations

15.

Lu, Laijun, et al.. (2020). Hyperspectral Band Selection for Lithologic Discrimination and Geological Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 471–486. 56 indexed citations

16.

Yang, Chen, et al.. (2018). Superpixel-Based Unsupervised Band Selection for Classification of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 56(12). 7230–7245. 43 indexed citations

17.

Li, Dan, William Yang, Yifan Zhang, et al.. (2018). Genomic analyses based on pulmonary adenocarcinoma in situ reveal early lung cancer signature. BMC Medical Genomics. 11(S5). 106–106. 24 indexed citations

18.

Yang, Mary Qu, et al.. (2018). MISC: missing imputation for single-cell RNA sequencing data. BMC Systems Biology. 12(S7). 114–114. 16 indexed citations

19.

Guan, Renchu, Xu Wang, Maurizio Marchese, et al.. (2018). Feature space learning model. Journal of Ambient Intelligence and Humanized Computing. 10(5). 2029–2040. 6 indexed citations

20.

Guan, Renchu, Xu Wang, Mary Qu Yang, et al.. (2018). Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways. Scientific Reports. 8(1). 267–267. 17 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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