Ruixin Yang

403 citations
10 papers · 231 · 1 hit paper · h-index 4

Impact in

Papers in

Ruixin Yang

9 papers receiving 225 citations

Ruixin Yang's Hit Papers

Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis 2021 · 200 citations
2000+1+3Years since publication50100150200

Peers

Ruixin Yang
Comparison fields: 5 of 80
  • Health Informatics 9
  • Computer Vision and Pattern Recognition 75
  • Radiology, Nuclear Medicine and Imaging 54
  • Neurology 14
  • Artificial Intelligence 57
Replace Marcus D. Bloice with:
Marcus D. Bloice Austria
Ştefan Holban Romania
Tohru Kamiya Japan
Khaled Harrar Algeria
Xuebo Liu China
Pradeep Kumar Singh India
Hamidullah Binol United States
Jilan Xu China
Biwen Lei China
Yanhong Luo China
Ruixin Yang relative to Marcus D. Bloice Austria Marcus D. Bloice's profile →
Citations per field
00.5×2.6×
Marcus D. Bloice · 1×
Citations per year

Countries citing papers authored by Ruixin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Ruixin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Ruixin Yang, 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 Ruixin Yang Line = papers co-authored together Ruixin Yang links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis
Hit paper breakdown →
2021200
2 20029
3 20028
4 20024
5 20243
6 20033
7 20222
8 20231
9 20191
10 20030

About Ruixin Yang

Ruixin Yang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Information Systems, having authored 10 papers that have together received 231 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (3 papers), Advanced Computational Techniques and Applications (3 papers), Data Management and Algorithms (3 papers), Distributed and Parallel Computing Systems (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Advanced Neural Network Applications (1 paper), Advanced Clustering Algorithms Research (1 paper) and Vehicle License Plate Recognition (1 paper). The work is most often cited by research in Health Informatics (9 citations), Computer Vision and Pattern Recognition (75 citations), Radiology, Nuclear Medicine and Imaging (54 citations), Neurology (14 citations) and Artificial Intelligence (57 citations). Ruixin Yang has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Yingyan Yu, M. Kafatos, Daniel Ziskin, Changzhou Wang, Changbing Yang, Dan Zhou, Zhilong Wu, Garrett Nicolai, Miikka Silfverberg and B. Doty. Their work appears in journals such as Sensors, Frontiers in Oncology, Computing in Science & Engineering and Data Science and Engineering.

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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