Linzhi Su

1.9k total citations · 1 hit paper
38 papers, 1.5k citations indexed

About

Linzhi Su is a scholar working on Media Technology, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering. According to data from OpenAlex, Linzhi Su has authored 38 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Media Technology, 13 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Biomedical Engineering. Recurrent topics in Linzhi Su's work include Remote-Sensing Image Classification (14 papers), Photoacoustic and Ultrasonic Imaging (12 papers) and Optical Imaging and Spectroscopy Techniques (12 papers). Linzhi Su is often cited by papers focused on Remote-Sensing Image Classification (14 papers), Photoacoustic and Ultrasonic Imaging (12 papers) and Optical Imaging and Spectroscopy Techniques (12 papers). Linzhi Su collaborates with scholars based in China, Australia and United States. Linzhi Su's co-authors include Maoguo Gong, Jia Liu, Puzhao Zhang, Licheng Jiao, Meng Jia, Weisheng Chen, Yue Wu, Wenping Ma, Zhizhou Li and Hao Li and has published in prestigious journals such as Journal of Applied Physics, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Linzhi Su

34 papers receiving 1.5k citations

Hit Papers

A Novel Point-Matching Algorithm Based on Fast Sample Con... 2014 2026 2018 2022 2014 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. A Novel Point-Matching Algorithm Based on Fast Sample Consensus for Image Registration
    2014 273 citations Maoguo Gong, Linzhi Su et al. profile →

Peers

Linzhi Su
Hongmin Gao China
Yuli Sun China
Lin Lei China
Junping Zhang China
Puhong Duan China
Srinivas Andra United States
Xin He China
Anzhu Yu China
Otávio A. B. Penatti Brazil
Hongmin Gao China
Linzhi Su
Citations per year, relative to Linzhi Su Linzhi Su (= 1×) peers Hongmin Gao

Countries citing papers authored by Linzhi Su

Since Specialization
Citations

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

Fields of papers citing papers by Linzhi Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linzhi Su

This figure shows the co-authorship network connecting the top 25 collaborators of Linzhi Su. A scholar is included among the top collaborators of Linzhi Su 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 Linzhi Su. Linzhi Su 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.
2.
Xu, Xueli, Jingyu Wang, Ping Zhou, et al.. (2024). EIDU-Net: edge-preserved inception DenseGCN U-Net for LiDAR point cloud segmentation. Scientific Reports. 14(1). 24620–24620. 1 indexed citations
3.
4.
Han, Xinxin, et al.. (2024). PointCluster: Deep Clustering of 3-D Point Clouds With Semantic Pseudo-Labeling. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–14. 2 indexed citations
5.
Chen, Yi, Kang Li, Fengjun Zhao, et al.. (2023). Regularized reconstruction based on joint smoothly clipped absolute deviation regularization and graph manifold learning for fluorescence molecular tomography. Physics in Medicine and Biology. 68(19). 195004–195004.
6.
Li, Kang, et al.. (2023). Logarithmic total variation regularization via preconditioned conjugate gradient method for sparse reconstruction of bioluminescence tomography. Computer Methods and Programs in Biomedicine. 243. 107863–107863. 5 indexed citations
7.
Chen, Yi, Linzhi Su, Huangjian Yi, et al.. (2022). ABPO-TVSCAD: alternating Bregman proximity operators approach based on TVSCAD regularization for bioluminescence tomography. Physics in Medicine and Biology. 67(21). 215013–215013. 4 indexed citations
8.
Wang, Jingyi, Yuxiang Zhang, Fengjun Zhao, et al.. (2022). PET/CT Based EGFR Mutation Status Classification of NSCLC Using Deep Learning Features and Radiomics Features. Frontiers in Pharmacology. 13. 898529–898529. 21 indexed citations
9.
Chen, Yi, Weitong Li, Linzhi Su, et al.. (2022). MSCN-NET: Multi-stage cascade neural network based on attention mechanism for Čerenkov luminescence tomography. Journal of Applied Physics. 132(17). 3 indexed citations
10.
Su, Linzhi, et al.. (2022). Change detection for multispectral images using modified semantic segmentation network. Journal of Applied Remote Sensing. 16(1). 2 indexed citations
11.
Cao, Xin, Lin Wang, Linzhi Su, et al.. (2019). A Novel Stacked Denoising Autoencoder-Based Reconstruction Framework for Cerenkov Luminescence Tomography. IEEE Access. 7. 85178–85189. 15 indexed citations
12.
Cao, Xin, Linzhi Su, Lin Wang, et al.. (2019). A fuzzy artificial neural network-based method for Cerenkov luminescence tomography. AIP Advances. 9(6). 4 indexed citations
13.
Gong, Maoguo, Linzhi Su, Hao Li, & Jia Liu. (2016). A Survey on Change Detection in Synthetic Aperture Radar Imagery. 53(1). 123. 8 indexed citations
14.
Zhang, Puzhao, Maoguo Gong, Linzhi Su, Jia Liu, & Zhizhou Li. (2016). Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing. 116. 24–41. 242 indexed citations
15.
Liu, Jia, Maoguo Gong, Qiguang Miao, Linzhi Su, & Hao Li. (2015). Change detection in synthetic aperture radar images based on unsupervised artificial immune systems. Applied Soft Computing. 34. 151–163. 10 indexed citations
16.
Wang, Qiao, Hao Li, Maoguo Gong, Linzhi Su, & Licheng Jiao. (2014). A multiobjective optimization method based on MOEA/D and fuzzy clustering for change detection in SAR images. 32. 3024–3029. 5 indexed citations
17.
Gong, Maoguo, et al.. (2014). SAR change detection based on intensity and texture changes. ISPRS Journal of Photogrammetry and Remote Sensing. 93. 123–135. 71 indexed citations
18.
Gong, Maoguo, Dayong Tian, Linzhi Su, & Licheng Jiao. (2014). An efficient bi-convex fuzzy variational image segmentation method. Information Sciences. 293. 351–369. 29 indexed citations
19.
Gong, Maoguo, Meng Jia, Linzhi Su, Shuang Wang, & Licheng Jiao. (2014). Detecting changes of the Yellow River Estuary via SAR images based on a local fit-search model and kernel-induced graph cuts. International Journal of Remote Sensing. 35(11-12). 4009–4030. 19 indexed citations
20.
Su, Linzhi, et al.. (2014). Change detection in synthetic aperture radar images based on non-local means with ratio similarity measurement. International Journal of Remote Sensing. 35(22). 7673–7690. 15 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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