Dong Zhao
- Artificial Intelligence top 1%
- Metaheuristic Optimization Algorithms Research 7
- Machine Learning and ELM 3
-
- Medical Image Segmentation Techniques 3
- Face recognition and analysis 3
- Media Technology top 5%
- Image Processing Techniques and Applications 4
-
- COVID-19 diagnosis using AI 6
-
- SARS-CoV-2 and COVID-19 Research 3
-
- Software Engineering Research 3
- Co-authors
- Huiling ChenAli Asghar HeidariLei LiuMajdi MafarjaHang SuXiaoqin ZhangFanhua YuZhennao Cai
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionComputational Theory and Mathematics
- Partner nations
- ChinaIranSaudi Arabia
In The Last Decade
Dong Zhao
47 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 906
- Computer Vision and Pattern Recognition 495
- Computational Theory and Mathematics 226
- Media Technology 98
- Radiology, Nuclear Medicine and Imaging 239
Countries citing papers authored by Dong Zhao
This map shows the geographic impact of Dong Zhao'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 Dong Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong Zhao more than expected).
Fields of papers citing papers by Dong Zhao
This network shows the impact of papers produced by Dong Zhao. 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 Dong Zhao. The network helps show where Dong Zhao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dong Zhao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | Artemisinin optimization based on malaria therapy: Algorithm and applications to medical image segmentationbreakdown → | 2024 | 65 |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 6 | |
| 6 | RIME: A physics-based optimizationbreakdown → | 2023 | 594 |
| 7 | 2023 | 8 | |
| 8 | 2023 | 17 | |
| 9 | 2023 | 25 | |
| 10 | 2023 | 21 | |
| 11 | 2022 | 5 | |
| 12 | Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentationbreakdown → | 2022 | 162 |
| 13 | 2022 | 5 | |
| 14 | 2022 | 50 | |
| 15 | 2022 | 17 | |
| 16 | 2021 | 78 | |
| 17 | 2021 | 1 | |
| 18 | Classroom Roll-Call System Based on ResNet Networks | 2020 | 1 |
| 19 | 2018 | 96 | |
| 20 | 2013 | 4 |
About Dong Zhao
Dong Zhao is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 50 papers that have together received 1.9k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (7 papers), COVID-19 diagnosis using AI (6 papers), Image Processing Techniques and Applications (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Software Engineering Research (3 papers), Machine Learning and ELM (3 papers), Medical Image Segmentation Techniques (3 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Artificial Intelligence (906 citations), Computer Vision and Pattern Recognition (495 citations) and Computational Theory and Mathematics (226 citations). Dong Zhao has collaborated with scholars based in China, Iran and Saudi Arabia. Frequent co-authors include Huiling Chen, Ali Asghar Heidari, Lei Liu, Majdi Mafarja, Hang Su, Xiaoqin Zhang, Fanhua Yu, Zhennao Cai, Zongda Wu and Mayun Chen. Their work appears in journals such as Scientific Reports, Chemical Physics Letters and Neurocomputing.
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.