Biao Wang

1.6k total citations · 1 hit paper
57 papers, 1.2k citations indexed

About

Biao Wang is a scholar working on Media Technology, Ecology and Atmospheric Science. According to data from OpenAlex, Biao Wang has authored 57 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Media Technology, 18 papers in Ecology and 17 papers in Atmospheric Science. Recurrent topics in Biao Wang's work include Remote-Sensing Image Classification (20 papers), Remote Sensing and Land Use (16 papers) and Remote Sensing in Agriculture (14 papers). Biao Wang is often cited by papers focused on Remote-Sensing Image Classification (20 papers), Remote Sensing and Land Use (16 papers) and Remote Sensing in Agriculture (14 papers). Biao Wang collaborates with scholars based in China, South Korea and United States. Biao Wang's co-authors include Yanlan Wu, Hui Yang, Penghai Wu, Jinglong Chen, Yanyang Zi, Zitong Zhou, Jun Pan, Jaewan Choi, Haochen Zhu and Jun Qin and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Biao Wang

52 papers receiving 1.1k citations

Hit Papers

LiftingNet: A Novel Deep Learning Network With Layerwise ... 2017 2026 2020 2023 2017 50 100 150 200 250
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. LiftingNet: A Novel Deep Learning Network With Layerwise Feature Learning From Noisy Mechanical Data for Fault Classification
    2017 257 citations Biao Wang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Biao Wang China 17 302 295 272 228 180 57 1.2k
Zhiqiang Du China 22 120 0.4× 501 1.7× 273 1.0× 206 0.9× 159 0.9× 93 1.9k
Xiao Xiao China 18 144 0.5× 86 0.3× 86 0.3× 110 0.5× 196 1.1× 269 1.4k
Maher Ibrahim Sameen Australia 21 161 0.5× 355 1.2× 194 0.7× 34 0.1× 294 1.6× 35 1.6k
Shuqing Zhang China 20 192 0.6× 147 0.5× 402 1.5× 68 0.3× 188 1.0× 91 1.1k
Ali Jamali Canada 20 249 0.8× 250 0.8× 292 1.1× 40 0.2× 156 0.9× 66 982
Linlin Xu Canada 24 502 1.7× 404 1.4× 219 0.8× 51 0.2× 626 3.5× 152 2.1k
Felix Schiefer Germany 7 173 0.6× 641 2.2× 731 2.7× 46 0.2× 124 0.7× 13 1.6k
Jalal Amini Iran 17 238 0.8× 431 1.5× 152 0.6× 106 0.5× 137 0.8× 78 986

Countries citing papers authored by Biao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Biao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Biao Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Biao Wang. A scholar is included among the top collaborators of Biao Wang 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 Biao Wang. Biao Wang 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.
Wang, Yingchun, et al.. (2025). A Mutual Information Constrained Multitask Learning Method for Very High-Resolution Building Segmentation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 9230–9243. 1 indexed citations
2.
Wang, Biao, et al.. (2025). Feature Enhancement and Feedback Network for Change Detection in Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters. 22. 1–5. 1 indexed citations
3.
Li, Yifan, et al.. (2025). Adaptive frequency attention-based interpretable Transformer network for few-shot fault diagnosis of rolling bearings. Reliability Engineering & System Safety. 263. 111271–111271. 7 indexed citations
4.
Yang, Hui, et al.. (2025). A high-resolution remote sensing land use/land cover classification method based on multi-level features adaptation of segment anything model. International Journal of Applied Earth Observation and Geoinformation. 141. 104659–104659. 1 indexed citations
5.
Li, Yan, et al.. (2024). Multisource High-Resolution Remote Sensing Image Vegetation Extraction with Comprehensive Multifeature Perception. Remote Sensing. 16(4). 712–712. 2 indexed citations
6.
Wang, Biao, et al.. (2024). Bridging the gap: The integration of eDNA techniques and traditional sampling in fish diversity analysis. Frontiers in Marine Science. 11. 9 indexed citations
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Wang, Biao, et al.. (2023). Analysis of YOLOv5 and DeepLabv3+ Algorithms for Detecting Illegal Cultivation on Public Land: A Case Study of a Riverside in Korea. International Journal of Environmental Research and Public Health. 20(3). 1770–1770. 4 indexed citations
10.
Wu, Penghai, et al.. (2023). Remote Sensing Crop Recognition by Coupling Phenological Features and Off-Center Bayesian Deep Learning. Remote Sensing. 15(3). 674–674. 12 indexed citations
11.
12.
Qin, Shugang, Yongan Liu, Yuting Chen, et al.. (2022). Engineered Bacteriophages Containing Anti-CRISPR Suppress Infection of Antibiotic-Resistant P. aeruginosa. Microbiology Spectrum. 10(5). e0160222–e0160222. 32 indexed citations
13.
Li, Mengya, et al.. (2021). A Deep Learning Method of Water Body Extraction From High Resolution Remote Sensing Images With Multisensors. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 3120–3132. 73 indexed citations
14.
Wang, Biao, et al.. (2020). Research on national security risk assessment model of open government data. SHILAP Revista de lepidopterología.
15.
Wang, Biao, et al.. (2019). China’s Digital Publishing Moving Towards In-Depth Integrated Development. Publishing Research Quarterly. 35(4). 648–669. 6 indexed citations
16.
Yan, Gao, Zeyu Liang, Biao Wang, Yanlan Wu, & Shiyu Liu. (2019). UAV and satellite remote sensing images based aboveground biomass inversion in the meadows of Lake Shengjin. Journal of Lake Sciences. 31(2). 517–528. 8 indexed citations
17.
Hu, Xianwei & Biao Wang. (2016). Land utilization classification based on CBERS-04 multispectral images--A case study in northwest Hainan, China. 47(10). 1813. 1 indexed citations
18.
Wang, Biao, et al.. (2013). Comparison of Change Detection Accuracy based on VHR images Corresponding to the Fusion Estimation Indexes. Journal of Korean Society for Geospatial Information Science. 21(2). 63–69.
19.
Zhang, Lijun, et al.. (2006). Acquisition Technique and I ts Effect of Complex Mountanious Region in Qaidam Bas in. Zhongguo shiyou kantan. 11(6). 51. 1 indexed citations
20.
Wang, Biao. (2004). Application of artificial neural network in rockmass quality classification. 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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