Xiurui Geng

1.5k total citations
79 papers, 1.2k citations indexed

About

Xiurui Geng is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xiurui Geng has authored 79 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Media Technology, 31 papers in Atmospheric Science and 22 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xiurui Geng's work include Remote-Sensing Image Classification (57 papers), Remote Sensing and Land Use (31 papers) and Advanced Image Fusion Techniques (22 papers). Xiurui Geng is often cited by papers focused on Remote-Sensing Image Classification (57 papers), Remote Sensing and Land Use (31 papers) and Advanced Image Fusion Techniques (22 papers). Xiurui Geng collaborates with scholars based in China, United States and France. Xiurui Geng's co-authors include Luyan Ji, Kang Sun, Yongchao Zhao, Peng Gong, Hairong Tang, Fuxiang Wang, Yun Lu, Kai Yu, Kang Jiang and Olivier Hagolle and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Xiurui Geng

76 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiurui Geng China 17 819 532 248 197 178 79 1.2k
Luyan Ji China 17 767 0.9× 532 1.0× 229 0.9× 254 1.3× 289 1.6× 75 1.2k
Andrea Marinoni Italy 19 958 1.2× 645 1.2× 244 1.0× 280 1.4× 128 0.7× 79 1.5k
Nicola Acito Italy 15 665 0.8× 292 0.5× 242 1.0× 193 1.0× 64 0.4× 78 992
Hsuan Ren United States 17 1.0k 1.2× 581 1.1× 257 1.0× 184 0.9× 78 0.4× 67 1.4k
Dariush Abbasi‐Moghadam Iran 16 337 0.4× 255 0.5× 143 0.6× 236 1.2× 168 0.9× 55 1.1k
Charles M. Bachmann United States 17 664 0.8× 333 0.6× 292 1.2× 423 2.1× 156 0.9× 89 1.4k
Kang Sun China 14 562 0.7× 384 0.7× 161 0.6× 83 0.4× 84 0.5× 31 755
Giovanna Trianni Italy 10 1.4k 1.8× 946 1.8× 360 1.5× 423 2.1× 317 1.8× 24 1.9k
Stefania Matteoli Italy 20 1.1k 1.3× 515 1.0× 246 1.0× 229 1.2× 75 0.4× 73 1.6k

Countries citing papers authored by Xiurui Geng

Since Specialization
Citations

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

Fields of papers citing papers by Xiurui Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiurui Geng

This figure shows the co-authorship network connecting the top 25 collaborators of Xiurui Geng. A scholar is included among the top collaborators of Xiurui Geng 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 Xiurui Geng. Xiurui Geng 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.
Gao, Jingyu, Xiurui Geng, & Luyan Ji. (2025). FastPSA: A Fast Version of the Principal Skewness Analysis. IEEE Signal Processing Letters. 32. 1226–1230. 1 indexed citations
2.
Zhu, Liangliang, et al.. (2025). Optimized Subset Selection for Matrices and its Application in Hyperspectral Band Selection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 6464–6479. 1 indexed citations
3.
Zhu, Xinwen, et al.. (2024). k ‐wise multi‐graph matching. IET Image Processing. 18(14). 4760–4777.
4.
Zhang, Yueting, et al.. (2024). FusionHeightNet: A Multi-Level Cross-Fusion Method from Multi-Source Remote Sensing Images for Urban Building Height Estimation. Remote Sensing. 16(6). 958–958. 6 indexed citations
5.
Ji, Luyan, et al.. (2024). Hyperspectral Band Selection via Joint Volume Gradient. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 17. 16535–16546. 1 indexed citations
6.
Geng, Xiurui, et al.. (2024). Hyperspectral Image Denoising Based on Principal-Third-Order-Moment Analysis. Remote Sensing. 16(2). 276–276. 3 indexed citations
7.
Zhu, Liangliang, Xinwen Zhu, & Xiurui Geng. (2023). Factorized multi-Graph matching. Pattern Recognition. 140. 109597–109597. 1 indexed citations
8.
Ji, Luyan & Xiurui Geng. (2023). Hyperspectral Target Detection Methods Based on Statistical Information: The Key Problems and the Corresponding Strategies. Remote Sensing. 15(15). 3835–3835. 2 indexed citations
9.
Zhu, Liangliang, et al.. (2023). Fast low-rank-matrix-based connection center evolution for large hyperspectral image clustering. Infrared Physics & Technology. 131. 104666–104666.
10.
Ji, Luyan, et al.. (2021). Hyperspectral target detection method based on filter tensor analysis. 1. 1 indexed citations
11.
Ji, Luyan, et al.. (2020). FastVGBS: A Fast Version of the Volume-Gradient-Based Band Selection Method for Hyperspectral Imagery. IEEE Geoscience and Remote Sensing Letters. 18(3). 514–517. 13 indexed citations
12.
Geng, Xiurui, et al.. (2020). A New Translation Matching Method Based on Autocorrelated Normalized Cross-Power Spectrum. IEEE Transactions on Geoscience and Remote Sensing. 59(8). 6956–6968. 3 indexed citations
13.
Xu, Ning, Hongjian You, Xiurui Geng, & Yingui Cao. (2016). Multi-task Jointly Sparse Spectral Unmixing Method Based on Spectral Similarity Measure of Hyperspectral Imagery. JOURNAL OF ELECTRONICS INFORMATION TECHNOLOGY. 38(11). 2708. 1 indexed citations
14.
Geng, Xiurui, Luyan Ji, & Kang Sun. (2016). Non-negative matrix factorization based unmixing for principal component transformed hyperspectral data. Frontiers of Information Technology & Electronic Engineering. 17(5). 403–412. 23 indexed citations
15.
Sun, Kang, et al.. (2015). A New Target Detection Method Using Nonlinear PCA for Hyperspectral Imagery. Bulletin of Surveying and Mapping. 105. 3 indexed citations
16.
Ji, Luyan, Xiurui Geng, Kang Sun, Yongchao Zhao, & Peng Gong. (2015). Target Detection Method for Water Mapping Using Landsat 8 OLI/TIRS Imagery. Water. 7(2). 794–817. 85 indexed citations
17.
Geng, Xiurui, Kang Sun, Luyan Ji, & Yongchao Zhao. (2014). A High-Order Statistical Tensor Based Algorithm for Anomaly Detection in Hyperspectral Imagery. Scientific Reports. 4(1). 6869–6869. 24 indexed citations
18.
Ji, Luyan, et al.. (2013). ハイパースペクトルリモートセンシングでの端成分抽出のための重心座標に基づく新しい非負値行列因数分解(BC-NMF)法. International Journal of Remote Sensing. 34. 6577–6586. 2 indexed citations
19.
Geng, Xiurui, Yongchao Zhao, Fuxiang Wang, & Peng Gong. (2010). A new volume formula for a simplex and its application to endmember extraction for hyperspectral image analysis. International Journal of Remote Sensing. 31(4). 1027–1035. 21 indexed citations
20.
Geng, Xiurui, et al.. (2004). Classification algorithm based on spatial continuity for hyperspectral image. JOURNAL OF INFRARED AND MILLIMETER WAVES. 23(4). 6 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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