Xi Ouyang

73 papers receiving 2.5k citations

Xi Ouyang's Hit Papers

A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory 2017 · 403 citations
4030+3+6Years since publication100200300400

Peers

Xi Ouyang
Comparison fields: 5 of 167
  • Health Informatics 109
  • Radiological and Ultrasound Technology 276
  • Radiology, Nuclear Medicine and Imaging 449
  • Artificial Intelligence 699
  • Computer Vision and Pattern Recognition 365
Replace Vitoantonio Bevilacqua with:
Vitoantonio Bevilacqua Italy
Mohammed Hossny Australia
Hyeran Byun South Korea
Yu Cao United States
Xuewei Li China
Marcin Grzegorzek Germany
Syed Saad Azhar Ali Malaysia
Hassan Khotanlou Iran
KONSTANTINOS MOUSTAKAS Greece
Tamer Abuhmed South Korea
Xi Ouyang relative to Vitoantonio Bevilacqua Italy Vitoantonio Bevilacqua's profile →
Citations per field
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Vitoantonio Bevilacqua · 1×
Citations per year

Countries citing papers authored by Xi Ouyang

Since Specialization
Citations

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

Fields of papers citing papers by Xi Ouyang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xi Ouyang, 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 Xi Ouyang Line = papers co-authored together Xi Ouyang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory
Hit paper breakdown →
2017403
2 2020292
3 2015175
4 2018171
5 2006114
6 2011112
7 2020101
8 201888
9 202486
10 200885
11 201769
12 202062
13 200959
14 201958
15 201956
16 201753
17 201832
18 202232
19 202130
20 202224

About Xi Ouyang

Xi Ouyang is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Health Informatics and Molecular Biology, having authored 74 papers that have together received 2.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), AI in cancer detection (11 papers), COVID-19 diagnosis using AI (6 papers), RNA modifications and cancer (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Lung Cancer Diagnosis and Treatment (4 papers), Sexual function and dysfunction studies (4 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Health Informatics (109 citations), Radiological and Ultrasound Technology (276 citations), Radiology, Nuclear Medicine and Imaging (449 citations), Artificial Intelligence (699 citations) and Computer Vision and Pattern Recognition (365 citations). Xi Ouyang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weili Fang, Peter E.D. Love, Hanbin Luo, Botao Zhong, Lieyun Ding, Pan Zhou, Qian Wang, Dinggang G. Shen, Lijun Liu and Junxia Chen. Their work appears in journals such as IEEE Transactions on Medical Imaging, Automation in Construction, Medical Image Analysis, Neuroscience and Journal of Material Science and Technology.

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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