Bo Dang

653 total citations · 1 hit paper
20 papers, 353 citations indexed

About

Bo Dang is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Ocean Engineering. According to data from OpenAlex, Bo Dang has authored 20 papers receiving a total of 353 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 6 papers in Media Technology and 3 papers in Ocean Engineering. Recurrent topics in Bo Dang's work include Remote-Sensing Image Classification (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Advanced Neural Network Applications (3 papers). Bo Dang is often cited by papers focused on Remote-Sensing Image Classification (6 papers), Advanced Image and Video Retrieval Techniques (4 papers) and Advanced Neural Network Applications (3 papers). Bo Dang collaborates with scholars based in China, United States and United Kingdom. Bo Dang's co-authors include Yansheng Li, Yongjun Zhang, Zhenhong Du, Yansheng Li, Danqing Ma, Xin Guo, Lixiang Ru, Huimei He, Ziyuan Huang and Yingying Zhang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Remote Sensing of Environment and IEEE Transactions on Image Processing.

In The Last Decade

Bo Dang

18 papers receiving 341 citations

Hit Papers

SkySense: A Multi-Modal Remote Sensing Foundation Model T... 2024 2026 2025 2024 25 50 75
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. SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery
    2024 96 citations Xin Guo, Jiangwei Lao et al. profile →

Peers

Bo Dang
Quanhua Zhao China
Xianjun Gao China
Liang Hong China
Estanislau Lima Brazil
Xizhe Xue China
Veronika Gstaiger Germany
Bo Cheng China
Yongmei Jiang China
Wenqing Feng China
Quanhua Zhao China
Bo Dang
Citations per year, relative to Bo Dang Bo Dang (= 1×) peers Quanhua Zhao

Countries citing papers authored by Bo Dang

Since Specialization
Citations

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

Fields of papers citing papers by Bo Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Dang

This figure shows the co-authorship network connecting the top 25 collaborators of Bo Dang. A scholar is included among the top collaborators of Bo Dang 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 Bo Dang. Bo Dang 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.
Li, Yansheng, Gong Cheng, Chao Tao, et al.. (2025). MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification With Zoom-Free Remote Sensing Imagery. IEEE/CAA Journal of Automatica Sinica. 12(5). 1004–1023. 10 indexed citations
2.
Chen, Wei, Lorenzo Bruzzone, Bo Dang, et al.. (2025). REST: Holistic Learning for End-to-End Semantic Segmentation of Whole-Scene Remote Sensing Imagery. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(1). 693–710. 2 indexed citations
3.
Li, Yansheng, Lei Yu, Bo Dang, et al.. (2025). Learning to reason over multi-granularity knowledge graph for zero-shot urban land-use mapping. Remote Sensing of Environment. 330. 114961–114961. 1 indexed citations
4.
Li, Yansheng, Bo Dang, Mang Ye, et al.. (2025). Unleashing the potential of remote sensing foundation models via bridging data and computility islands. The Innovation. 6(6). 100841–100841. 1 indexed citations
5.
Wu, Kang, Yingying Zhang, Lixiang Ru, et al.. (2025). A semantic-enhanced multi-modal remote sensing foundation model for Earth observation. Nature Machine Intelligence. 7(8). 1235–1249. 5 indexed citations
6.
Li, Yansheng, Xue Yang, Qi Wang, et al.. (2024). STAR: A First-Ever Dataset and a Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(3). 1832–1849. 23 indexed citations
7.
Li, Yansheng, Bo Dang, Wanchun Li, & Yongjun Zhang. (2024). GLH-Water: A Large-Scale Dataset for Global Surface Water Detection in Large-Size Very-High-Resolution Satellite Imagery. Proceedings of the AAAI Conference on Artificial Intelligence. 38(20). 22213–22221. 17 indexed citations
8.
Dang, Bo, Yansheng Li, Yongjun Zhang, & Jiayi Ma. (2024). Progressive Learning With Cross-Window Consistency for Semi-Supervised Semantic Segmentation. IEEE Transactions on Image Processing. 33. 5219–5231. 5 indexed citations
9.
10.
Guo, Xin, Jiangwei Lao, Bo Dang, et al.. (2024). SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery. 27662–27673. 96 indexed citations breakdown →
11.
Dang, Bo, et al.. (2024). Real-Time Pill Identification for the Visually Impaired Using Deep Learning. 552–555. 19 indexed citations
12.
Dang, Bo, et al.. (2024). Deep learning-based snore sound analysis for the detection of night-time breathing disorders. Applied and Computational Engineering. 76(1). 109–114. 14 indexed citations
13.
14.
Dang, Bo, et al.. (2024). Enhancing Kitchen Independence: Deep Learning-Based Object Detection for Visually Impaired Assistance. Academic Journal of Science and Technology. 9(2). 180–184. 5 indexed citations
15.
Wang, Yu, et al.. (2022). DNAS: Decoupling Neural Architecture Search for High-Resolution Remote Sensing Image Semantic Segmentation. Remote Sensing. 14(16). 3864–3864. 8 indexed citations
16.
Li, Yansheng, Bo Dang, Yongjun Zhang, & Zhenhong Du. (2022). Water body classification from high-resolution optical remote sensing imagery: Achievements and perspectives. ISPRS Journal of Photogrammetry and Remote Sensing. 187. 306–327. 74 indexed citations
17.
Dang, Bo & Yansheng Li. (2021). MSResNet: Multiscale Residual Network via Self-Supervised Learning for Water-Body Detection in Remote Sensing Imagery. Remote Sensing. 13(16). 3122–3122. 43 indexed citations
18.
Sun, Xian, Peijin Wang, Zhiyuan Yan, et al.. (2021). Automated High-Resolution Earth Observation Image Interpretation: Outcome of the 2020 Gaofen Challenge. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 8922–8940. 16 indexed citations
19.
20.
Tang, Xianfeng, Zhaoyun Duan, Bo Dang, et al.. (2012). Ellipse-shaped electron gun for W-band sheet beam devices. 385–386. 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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