Yingda Xia

3.2k citations
12 papers · 548 · h-index 8

Impact in

Papers in

Yingda Xia

11 papers receiving 544 citations

Peers

Yingda Xia
Comparison fields: 5 of 58
  • Computer Vision and Pattern Recognition 312
  • Radiology, Nuclear Medicine and Imaging 216
  • Artificial Intelligence 269
  • Neurology 63
  • Health Informatics 10
Replace Zizhou Wang with:
Zizhou Wang China
Ikram Ullah Lali Pakistan
Zhe Xu China
Yujiro Furukawa Japan
Tianyu Shi China
Adnan N. Qureshi Pakistan
Hengfei Cui China
Fengbei Liu Australia
Wessam M. Salama Egypt
Xintong Li China
Yingda Xia relative to Zizhou Wang China Zizhou Wang's profile →
Citations per field
00.5×
Zizhou Wang · 1×
Citations per year

Countries citing papers authored by Yingda Xia

Since Specialization
Citations

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

Fields of papers citing papers by Yingda Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yingda Xia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yingda Xia Line = papers co-authored together Yingda Xia links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2020172
2 2022122
3 201896
4 202095
5 202319
6
A 3D Coarse-to-Fine Framework for Automatic Pancreas Segmentation.
201717
7 201911
8 20247
9 20244
10
Thickened 2D Networks for 3D Medical Image Segmentation.
20193
11
Bridging the Gap Between 2D and 3D Organ Segmentation.
20182
12 20260

About Yingda Xia

Yingda Xia is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine and Epidemiology, having authored 12 papers that have together received 548 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Medical Image Segmentation Techniques (7 papers), COVID-19 diagnosis using AI (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging Techniques and Applications (1 paper), Industrial Vision Systems and Defect Detection (1 paper) and Medical Imaging and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (312 citations), Radiology, Nuclear Medicine and Imaging (216 citations), Artificial Intelligence (269 citations), Neurology (63 citations) and Health Informatics (10 citations). Yingda Xia has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Alan Yuille, Zhuotun Zhu, Dong Yang, Fengze Liu, Daguang Xu, Jinzheng Cai, Holger R. Roth, Lequan Yu, Elliot K. Fishman and Wei Shen. Their work appears in journals such as Nature Communications, IEEE Transactions on Neural Networks and Learning Systems, Medical Image Analysis, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

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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