Tiejun Yang
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
-
- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Face and Expression Recognition
- Digital Imaging for Blood Diseases
Papers in
-
- Face and Expression Recognition 10
- Medical Image Segmentation Techniques 7
- Advanced Neural Network Applications 5
-
- Machine Learning and ELM 6
- Co-authors
- Chunhua Zhu (5 shared papers)Lei Li (1 shared paper)Jianyu Miao (11 shared papers)Tingting Wu (1 shared paper)Lei Li (4 shared papers)Xuan Fei (3 shared papers)Yong Shi (4 shared papers)Lingfeng Niu (3 shared papers)
- Journals
- Journal of X-Ray Science and Technology (3 papers)Expert Systems with Applications (3 papers)Journal of Applied Clinical Medical Physics (2 papers)Pattern Recognition (2 papers)Optik (2 papers)
- Partner nations
- ChinaUnited StatesIran
In The Last Decade
Tiejun Yang
41 papers receiving 459 citations
Peers
Comparison fields: 5 of 88
- Neurology 110
- Computer Vision and Pattern Recognition 224
- Radiology, Nuclear Medicine and Imaging 108
- Artificial Intelligence 139
- Ophthalmology 22
Countries citing papers authored by Tiejun Yang
This map shows the geographic impact of Tiejun 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 Tiejun Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiejun Yang more than expected).
Fields of papers citing papers by Tiejun Yang
This network shows the impact of papers produced by Tiejun 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 Tiejun Yang. The network helps show where Tiejun Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Tiejun Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 67 | |
| 2 | 2020 | 55 | |
| 3 | 2021 | 54 | |
| 4 | 2021 | 40 | |
| 5 | 2020 | 28 | |
| 6 | 2019 | 21 | |
| 7 | 2023 | 19 | |
| 8 | 2019 | 17 | |
| 9 | 2018 | 15 | |
| 10 | 2022 | 15 | |
| 11 | 2021 | 13 | |
| 12 | 2016 | 10 | |
| 13 | 2022 | 10 | |
| 14 | 2023 | 9 | |
| 15 | 2016 | 9 | |
| 16 | 2010 | 9 | |
| 17 | 2020 | 9 | |
| 18 | 2024 | 8 | |
| 19 | 2021 | 7 | |
| 20 | 2020 | 6 |
About Tiejun Yang
Tiejun Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Computational Mechanics, having authored 46 papers that have together received 472 indexed citations. Recurring topics across this work include Face and Expression Recognition (10 papers), Medical Image Segmentation Techniques (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Machine Learning and ELM (6 papers), Spectroscopy and Chemometric Analyses (5 papers), Advanced Neural Network Applications (5 papers), Brain Tumor Detection and Classification (5 papers) and Advanced Wireless Communication Techniques (5 papers). The work is most often cited by research in Neurology (110 citations), Computer Vision and Pattern Recognition (224 citations), Radiology, Nuclear Medicine and Imaging (108 citations), Artificial Intelligence (139 citations) and Ophthalmology (22 citations). Tiejun Yang has collaborated with scholars based in China, United States and Iran. Frequent co-authors include Chunhua Zhu, Lei Li, Jianyu Miao, Tingting Wu, Lei Li, Xuan Fei, Yong Shi, Lingfeng Niu, Lijun Sun and Junwei Jin. Their work appears in journals such as Journal of X-Ray Science and Technology, Expert Systems with Applications, Journal of Applied Clinical Medical Physics, Pattern Recognition and Optik.
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.