Baipeng Li

449 total citations · 1 hit paper
9 papers, 341 citations indexed

About

Baipeng Li is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Global and Planetary Change. According to data from OpenAlex, Baipeng Li has authored 9 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Media Technology, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Global and Planetary Change. Recurrent topics in Baipeng Li's work include Remote-Sensing Image Classification (5 papers), Remote Sensing in Agriculture (2 papers) and Land Use and Ecosystem Services (2 papers). Baipeng Li is often cited by papers focused on Remote-Sensing Image Classification (5 papers), Remote Sensing in Agriculture (2 papers) and Land Use and Ecosystem Services (2 papers). Baipeng Li collaborates with scholars based in China and Australia. Baipeng Li's co-authors include Zhengchao Chen, Pan Chen, Bing Zhang, Danfeng Hong, Xuan Yang, Bing Zhang, Xuan Yang, Jocelyn Chanussot, Pan Chen and Xiuping Jia and has published in prestigious journals such as Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing and Landslides.

In The Last Decade

Baipeng Li

7 papers receiving 337 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.

FCCDN: Feature constraint network for VHR image change detection

2022 153 citations Pan Chen, Bing Zhang et al. ISPRS Journal of Photogrammetry and Remote Sensing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Baipeng Li China	6	253	125	103	89	52	9	341
Qingyang Li China	6	247 1.0×	163 1.3×	88 0.9×	81 0.9×	59 1.1×	12	376
Jihui Tu China	11	156 0.6×	97 0.8×	84 0.8×	47 0.5×	33 0.6×	34	335
Shuhei Hikosaka Japan	7	181 0.7×	105 0.8×	74 0.7×	55 0.6×	63 1.2×	9	290
Benqin Song China	8	262 1.0×	176 1.4×	90 0.9×	85 1.0×	42 0.8×	11	344
Tianyi Jia China	5	239 0.9×	135 1.1×	81 0.8×	76 0.9×	28 0.5×	7	345
Huiwei Jiang China	6	282 1.1×	212 1.7×	68 0.7×	124 1.4×	49 0.9×	9	395
Muying Luo China	7	182 0.7×	73 0.6×	109 1.1×	56 0.6×	82 1.6×	12	316
Pengyuan Lv China	9	290 1.1×	175 1.4×	138 1.3×	104 1.2×	61 1.2×	21	410
Lucas Drumetz France	11	262 1.0×	174 1.4×	50 0.5×	57 0.6×	48 0.9×	38	402

Countries citing papers authored by Baipeng Li

Since Specialization

Citations

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

Fields of papers citing papers by Baipeng Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baipeng Li

This figure shows the co-authorship network connecting the top 25 collaborators of Baipeng Li. A scholar is included among the top collaborators of Baipeng Li 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 Baipeng Li. Baipeng Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Wu, Hongan, Yonghong Zhang, Ying Liu, et al.. (2025). A traceability investigation of the 2023 Xinjing open-pit coal mine landslide: remote sensing analysis using spaceborne SAR and optical imagery. Landslides. 23(2). 399–416.

2.

Li, Baipeng, et al.. (2025). Large-Scale Individual Plastic Greenhouse Extraction Using Deep Learning and High-Resolution Remote Sensing Imagery. Agronomy. 15(8). 2014–2014.

3.

Chen, Pan, Bing Zhang, Danfeng Hong, et al.. (2022). FCCDN: Feature constraint network for VHR image change detection. ISPRS Journal of Photogrammetry and Remote Sensing. 187. 101–119. 153 indexed citations breakdown →

4.

Zhang, Hao, et al.. (2022). An Operational Atmospheric Correction Framework for Multi-Source Medium-High-Resolution Remote Sensing Data of China. Remote Sensing. 14(21). 5590–5590. 7 indexed citations

5.

Yang, Xuan, Zhengchao Chen, Bing Zhang, et al.. (2022). A Block Shuffle Network with Superpixel Optimization for Landsat Image Semantic Segmentation. Remote Sensing. 14(6). 1432–1432. 5 indexed citations

6.

Yang, Xuan, Shanshan Li, Zhengchao Chen, et al.. (2021). An attention-fused network for semantic segmentation of very-high-resolution remote sensing imagery. ISPRS Journal of Photogrammetry and Remote Sensing. 177. 238–262. 136 indexed citations

7.

Li, Qingting, Zhengchao Chen, Bing Zhang, et al.. (2020). Detection of Tailings Dams Using High-Resolution Satellite Imagery and a Single Shot Multibox Detector in the Jing–Jin–Ji Region, China. Remote Sensing. 12(16). 2626–2626. 28 indexed citations

8.

Chen, Zhengchao, Lianru Gao, Baipeng Li, et al.. (2019). Automatic Detection of Track and Fields in China from High-Resolution Satellite Images Using Multi-Scale-Fused Single Shot MultiBox Detector. Remote Sensing. 11(11). 1377–1377. 3 indexed citations

9.

Yang, Xuan, Zhengchao Chen, Baipeng Li, et al.. (2019). A Fast and Precise Method for Large-Scale Land-Use Mapping Based on Deep Learning. 9 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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