Songze Tang

558 citations
22 papers · 466 indexed · 1 hit paper · h-index 8
Topics
Image and Signal Denoising Methods (16 papers)Advanced Image Fusion Techniques (13 papers)Advanced Image Processing Techniques (9 papers)
Journals
SHILAP Revista de lepidopterologíaRemote SensingIEEE Geoscience and Remote Sensing Letters

In The Last Decade

Songze Tang

21 papers receiving 456 citations

Hit Papers

A New Pan-Sharpening Method With Deep Neural Networks2015202620182022201550100150200250

Peers

Songze Tang
Comparison fields: 5 of 53
  • Media Technology 401
  • Computer Vision and Pattern Recognition 283
  • Atmospheric Science 89
  • Biomedical Engineering 39
  • Ecology 37
Replace M.T. Eismann with:
M.T. Eismann United States
Yunpeng Bai China
Xiangyu Liu China
Randi Fu China
Shuguo Jiang China
Jie Xie China
Shengwei Zhong China
Todd Wittman United States
Songze Tang relative to M.T. Eismann United States M.T. Eismann's profile →
Citations per field
00.5×3.5×
M.T. Eismann · 1×
Citations per year

Countries citing papers authored by Songze Tang

Since Specialization
Citations

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

Fields of papers citing papers by Songze Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Songze Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Songze Tang. A scholar is included among the top collaborators of Songze Tang 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 Songze Tang. Songze Tang 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
#WorkIndexed citations
1 24
2 1
3 10
4 31
5 66
6 9
7 2
8 2
9 0
10 6
11 2
12 7
13 2
14 2
15 1
16
A New Pan-Sharpening Method With Deep Neural Networksbreakdown →
269
17 2
18 5
19 6
20 4

About Songze Tang

Songze Tang is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Atmospheric Science, having authored 22 papers that have together received 466 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (16 papers), Advanced Image Fusion Techniques (13 papers) and Advanced Image Processing Techniques (9 papers). The work is most often cited by research in Media Technology (401 citations), Computer Vision and Pattern Recognition (283 citations) and Atmospheric Science (89 citations). Songze Tang has collaborated with scholars based in China, Australia and South Korea. Frequent co-authors include Liang Xiao, Wei Huang, Zhihui Wei, Hongyi Liu, Le Sun, Tianming Zhan, Xu Bin, Yuhui Zheng, Pengfei Liu and Zhenqiu Shu. Their work appears in journals such as SHILAP Revista de lepidopterología, Remote Sensing and IEEE Geoscience and Remote Sensing Letters.

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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