Shiao Xie

550 citations
11 papers · 320 indexed · 1 hit paper · h-index 4
Topics
Advanced Neural Network Applications (7 papers)Domain Adaptation and Few-Shot Learning (6 papers)AI in cancer detection (5 papers)
Journals
arXiv (Cornell University)Proceedings of the AAAI Conference on Artificial IntelligenceProceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Partner nations
ChinaJapanCanada

In The Last Decade

Shiao Xie

11 papers receiving 320 citations

Hit Papers

Mixed Transformer U-Net for Medical Image Segmentation2022202620232024202250100150200

Peers

Shiao Xie
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 223
  • Artificial Intelligence 107
  • Radiology, Nuclear Medicine and Imaging 101
  • Neurology 89
  • Biomedical Engineering 46
Replace Jieru Mei with:
Jieru Mei United States
Hongchun Lu China
Junlong Cheng China
Changfa Shi China
Ange Lou United States
Chengrui Gao China
Annegreet van Opbroek Netherlands
Milad Soltany Canada
S. J. Pawan India
Yuanming Gao China
Shiao Xie relative to Jieru Mei United States Jieru Mei's profile →
Citations per field
00.5×9.1×
Jieru Mei · 1×
Citations per year

Countries citing papers authored by Shiao Xie

Since Specialization
Citations

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

Fields of papers citing papers by Shiao Xie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiao Xie

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 1
2 1
3 2
4 3
5 1
6 1
7 2
8 7
9 21
10 68
11
Mixed Transformer U-Net for Medical Image Segmentationbreakdown →
213

About Shiao Xie

Shiao Xie is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology, having authored 11 papers that have together received 320 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Domain Adaptation and Few-Shot Learning (6 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (223 citations), Neurology (89 citations) and Radiology, Nuclear Medicine and Imaging (101 citations). Shiao Xie has collaborated with scholars based in China, Japan and Canada. Frequent co-authors include Yen‐Wei Chen, Lanfen Lin, Ruofeng Tong, Yutaro Iwamoto, Xian‐Hua Han, Hongyi Wang, Huimin Huang, Yawen Huang, Yuexiang Li and Yefeng Zheng. Their work appears in journals such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.

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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