Hongmin Gao

2.8k total citations · 1 hit paper
173 papers, 2.0k citations indexed

About

Hongmin Gao is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hongmin Gao has authored 173 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 93 papers in Media Technology, 55 papers in Atmospheric Science and 52 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hongmin Gao's work include Remote-Sensing Image Classification (85 papers), Remote Sensing and Land Use (55 papers) and Advanced Image Fusion Techniques (44 papers). Hongmin Gao is often cited by papers focused on Remote-Sensing Image Classification (85 papers), Remote Sensing and Land Use (55 papers) and Advanced Image Fusion Techniques (44 papers). Hongmin Gao collaborates with scholars based in China, Indonesia and Australia. Hongmin Gao's co-authors include Chenming Li, Zhonghao Chen, Bing Zhang, Yao Yang, Danfeng Hong, Yiyan Zhang, Feng Xu, Lianru Gao, Xin Li and Xin Lyu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Hongmin Gao

145 papers receiving 2.0k citations

Hit Papers

A Frequency Decoupling Network for Semantic Segmentation ... 2025 2026 2025 5 10 15 20 25

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hongmin Gao China 27 1.2k 598 576 265 239 173 2.0k
Puhong Duan China 27 1.5k 1.3× 580 1.0× 793 1.4× 304 1.1× 230 1.0× 88 2.2k
Mingyang Zhang China 27 1.1k 0.9× 682 1.1× 515 0.9× 512 1.9× 142 0.6× 118 2.0k
Lin Lei China 24 1.2k 1.0× 475 0.8× 1.0k 1.8× 332 1.3× 437 1.8× 108 2.3k
Xin Wu China 18 1.3k 1.1× 491 0.8× 975 1.7× 282 1.1× 636 2.7× 61 2.4k
Ping Zhong China 24 1.9k 1.6× 907 1.5× 1.0k 1.8× 478 1.8× 328 1.4× 82 2.7k
Xin He China 23 1.1k 0.9× 588 1.0× 623 1.1× 357 1.3× 119 0.5× 84 2.2k
Xiaofei Yang China 18 794 0.7× 402 0.7× 410 0.7× 216 0.8× 92 0.4× 98 1.8k
Bing Tu China 32 1.7k 1.4× 926 1.5× 717 1.2× 396 1.5× 185 0.8× 157 2.8k
Liguo Wang China 27 1.8k 1.5× 1.0k 1.7× 780 1.4× 289 1.1× 147 0.6× 226 2.7k
Junping Zhang China 20 1.2k 1.0× 546 0.9× 632 1.1× 171 0.6× 213 0.9× 167 1.7k

Countries citing papers authored by Hongmin Gao

Since Specialization
Citations

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

Fields of papers citing papers by Hongmin Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongmin Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Hongmin Gao. A scholar is included among the top collaborators of Hongmin Gao 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 Hongmin Gao. Hongmin Gao 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.
Chen, Zhonghao, Hongmin Gao, Yiyan Zhang, et al.. (2025). MDA-HTD: Mask-driven dual autoencoders meet hyperspectral target detection. Information Processing & Management. 62(4). 104106–104106. 8 indexed citations
2.
Zhang, Yiyan, et al.. (2025). Adaptive multi-stage fusion of hyperspectral and LiDAR data via selective state space models. Information Fusion. 125. 103488–103488. 1 indexed citations
3.
Zhang, Yiyan, et al.. (2025). E-Mamba: Efficient Mamba network for hyperspectral and LiDAR joint classification. Information Fusion. 126. 103649–103649. 1 indexed citations
4.
Gao, Hongmin, et al.. (2024). Secure collaborative EHR Sharing using multi-authority attribute-based proxy re-encryption in Web 3.0. Computer Networks. 255. 110851–110851. 4 indexed citations
6.
Li, Xin, Tao Li, Yao Tong, et al.. (2024). A Spectral–Spatial Context-Boosted Network for Semantic Segmentation of Remote Sensing Images. Remote Sensing. 16(7). 1214–1214. 15 indexed citations
7.
Ding, Xuewen, et al.. (2024). Dual-Feature Attention-Based Contrastive Prototypical Clustering for Multimodal Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–13. 4 indexed citations
8.
Geng, S., et al.. (2024). Cognitive Fusion of Graph Neural Network and Convolutional Neural Network for Enhanced Hyperspectral Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 8 indexed citations
9.
Chen, Xu, et al.. (2024). Airborne Small Target Detection Method Based on Multimodal and Adaptive Feature Fusion. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–15. 10 indexed citations
10.
Chen, Zhonghao, Guoyong Wu, Hongmin Gao, et al.. (2023). Local aggregation and global attention network for hyperspectral image classification with spectral-induced aligned superpixel segmentation. Expert Systems with Applications. 232. 120828–120828. 63 indexed citations
11.
Wang, Longbao, et al.. (2023). A CBAM‐GAN‐based method for super‐resolution reconstruction of remote sensing image. IET Image Processing. 18(2). 548–560. 4 indexed citations
12.
Gao, Hongmin, et al.. (2023). AMSSE-Net: Adaptive Multiscale Spatial–Spectral Enhancement Network for Classification of Hyperspectral and LiDAR Data. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–17. 46 indexed citations
13.
Li, Chenming, et al.. (2023). Adaptively Dictionary Construction for Hyperspectral Target Detection. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 13 indexed citations
14.
Zhang, Yiyan, Yongfeng Zhou, Danfeng Hong, et al.. (2023). Depthwise Separable Convolutional Autoencoders for Hyperspectral Image Change Detection. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 14 indexed citations
15.
Zhang, Yiyan, et al.. (2023). A dual-branch siamese spatial-spectral transformer attention network for Hyperspectral Image Change Detection. Expert Systems with Applications. 238. 122125–122125. 18 indexed citations
16.
Li, Chenming, et al.. (2023). A novel dimensionality reduction algorithm for Cholangiocarcinoma hyperspectral images. Optics & Laser Technology. 167. 109689–109689. 9 indexed citations
17.
Chen, Zhonghao, Hongmin Gao, Yiyan Zhang, et al.. (2022). Global to Local: A Hierarchical Detection Algorithm for Hyperspectral Image Target Detection. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–15. 69 indexed citations
18.
Wang, Biao, et al.. (2021). Equivalent Test Method for Strong Electromagnetic Field Radiation Effect of EED. International Journal of Antennas and Propagation. 2021. 1–9. 5 indexed citations
19.
Li, Chenming, et al.. (2017). Research on Fault Diagnosis for Pumping Station Based on T-S Fuzzy Fault Tree and Bayesian Network. Journal of Electrical and Computer Engineering. 2017. 1–7. 13 indexed citations
20.
Zhou, Hui, et al.. (2013). A Super-resolution Reconstruction Method of Remotely Sensed Image Based on Sparse Representation. SHILAP Revista de lepidopterología. 1 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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