Xuchu Yu

2.2k total citations · 1 hit paper
52 papers, 1.8k citations indexed

About

Xuchu Yu is a scholar working on Media Technology, Atmospheric Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Xuchu Yu has authored 52 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Media Technology, 42 papers in Atmospheric Science and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Xuchu Yu's work include Remote-Sensing Image Classification (49 papers), Remote Sensing and Land Use (42 papers) and Advanced Image Fusion Techniques (13 papers). Xuchu Yu is often cited by papers focused on Remote-Sensing Image Classification (49 papers), Remote Sensing and Land Use (42 papers) and Advanced Image Fusion Techniques (13 papers). Xuchu Yu collaborates with scholars based in China and Russia. Xuchu Yu's co-authors include Bing Liu, Anzhu Yu, Pengqiang Zhang, Xiong Tan, Kuiliang Gao, Xiangpo Wei, Ruirui Wang, Gang Wan, Zhixiang Xue and Yifan Sun 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

Xuchu Yu

49 papers receiving 1.8k 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.

Deep Few-Shot Learning for Hyperspectral Image Classification

2018 330 citations Bing Liu, Xuchu Yu et al. IEEE Transactions on Geoscience and Remote Sensing profile →

Peers

Xuchu Yu

MT

AS

CVPR

AI

ECOLO

Xianghai Cao China

Nanjun He China

Li Wei China

Le Sun China

Xia Xu China

Hanlu Jiang China

Anzhu Yu China

Qiong Ran China

Zhu Han China

Xianghai Cao China

Xuchu Yu

1.2k ×0.8

MT

736 ×0.7

AS

455 ×0.8

CVPR

273 ×0.8

AI

135 ×0.9

ECOLO

Citations per year, relative to Xuchu Yu Xuchu Yu (= 1×) peers Xianghai Cao

Countries citing papers authored by Xuchu Yu

Since Specialization

Citations

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

Fields of papers citing papers by Xuchu Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xuchu Yu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Xue, Zhixiang, et al.. (2024). Multimodal self-supervised learning for remote sensing data land cover classification. Pattern Recognition. 157. 110959–110959. 15 indexed citations

2.

Liu, Bing, et al.. (2024). Large multimodal model for open vocabulary semantic segmentation of remote sensing images. European Journal of Remote Sensing. 58(1). 1 indexed citations

3.

Liu, Bing, et al.. (2023). Deep hierarchical transformer for change detection in high-resolution remote sensing images. European Journal of Remote Sensing. 56(1). 8 indexed citations

4.

Liu, Bing, Anzhu Yu, Kuiliang Gao, et al.. (2022). DSS-TRM: deep spatial–spectral transformer for hyperspectral image classification. European Journal of Remote Sensing. 55(1). 103–114. 42 indexed citations

5.

Gao, Kuiliang, Bing Liu, Xuchu Yu, & Anzhu Yu. (2022). Unsupervised Meta Learning With Multiview Constraints for Hyperspectral Image Small Sample set Classification. IEEE Transactions on Image Processing. 31. 3449–3462. 59 indexed citations

6.

Sun, Yifan, Bing Liu, Xuchu Yu, et al.. (2022). Perceiving Spectral Variation: Unsupervised Spectrum Motion Feature Learning for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–17. 117 indexed citations

7.

Sun, Yifan, Bing Liu, Xuchu Yu, et al.. (2022). From Video to Hyperspectral: Hyperspectral Image-Level Feature Extraction with Transfer Learning. Remote Sensing. 14(20). 5118–5118. 14 indexed citations

8.

Yu, Xuchu, et al.. (2022). FSL-EGNN: Edge-Labeling Graph Neural Network for Hyperspectral Image Few-Shot Classification. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–18. 27 indexed citations

9.

Gao, Kuiliang, et al.. (2020). Deep Relation Network for Hyperspectral Image Few-Shot Classification. Remote Sensing. 12(6). 923–923. 146 indexed citations

10.

Gao, Kuiliang, Wenyue Guo, Xuchu Yu, et al.. (2020). Deep Induction Network for Small Samples Classification of Hyperspectral Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 3462–3477. 32 indexed citations

11.

Zhang, Pengqiang, et al.. (2020). Generative adversarial networks for hyperspectral image classification. Bulletin of Surveying and Mapping. 29. 2 indexed citations

12.

Liu, Bing, Anzhu Yu, Xuchu Yu, et al.. (2020). Deep Multiview Learning for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 59(9). 7758–7772. 109 indexed citations

13.

Yu, Xuchu, et al.. (2020). Graph inductive learning method for small sample classification of hyperspectral remote sensing images. European Journal of Remote Sensing. 53(1). 349–357. 6 indexed citations

14.

Yu, Xuchu, et al.. (2018). Deep 3D convolutional network combined with spatial-spectral features for hyperspectral image classification. SHILAP Revista de lepidopterología. 16 indexed citations

15.

Wei, Xiangpo, et al.. (2017). Import Vector Machine Based Hyperspectral Imagery Classification. Procedia Computer Science. 107. 861–866. 1 indexed citations

16.

Chen, Wei, Xuchu Yu, Pengqiang Zhang, & He Wang. (2012). PSO-based endmembers extraction algorithm for hyperspectral imagery. Computer Engineering and Applications Journal. 48(8). 189–193. 2 indexed citations

17.

Yu, Xuchu, et al.. (2009). Using of geospatial video surveillance networks for urban security and emergency applications. 83. 1–5. 2 indexed citations

18.

Yu, Xuchu, et al.. (2008). Hyperspectral Remote Sensing Image Classification Based on Kernel Fisher Discriminant Analysis. National Remote Sensing Bulletin. 0(4). 579–585. 1 indexed citations

19.

Yu, Xuchu, et al.. (2007). Hyperspectral image feature extraction based on nonlinear discriminate analysis. Cehui kexue. 32(5). 91–93. 1 indexed citations

20.

Zhang, Pengqiang, et al.. (2006). A Study on Relative Radiometric Correction of Multitemporal Remote Sensing Images. National Remote Sensing Bulletin. 0(3). 339–344. 8 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.

Explore authors with similar magnitude of impact