Dongze Lian
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Computer Networks and Communications top 2%
- Biomedical Engineering top 10%
- Epidemiology
- Co-authors
- Shenghua GaoWeixin LuoWen LiuLixin DuanJia ZhengJing LiJinhui TangXi Peng
- Topics
- Human Pose and Action Recognition (9 papers)Multimodal Machine Learning Applications (7 papers)Anomaly Detection Techniques and Applications (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Networks and Communications
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Neural Networks and Learning SystemsThe Visual Computer
- Partner nations
- ChinaSingaporeUnited Kingdom
In The Last Decade
Dongze Lian
21 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 85
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 870
- Computer Networks and Communications 687
- Biomedical Engineering 312
- Epidemiology 143
Countries citing papers authored by Dongze Lian
This map shows the geographic impact of Dongze Lian'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 Dongze Lian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongze Lian more than expected).
Fields of papers citing papers by Dongze Lian
This network shows the impact of papers produced by Dongze Lian. 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 Dongze Lian. The network helps show where Dongze Lian may publish in the future.
Co-authorship network of co-authors of Dongze Lian
This figure shows the co-authorship network connecting the top 25 collaborators of Dongze Lian. A scholar is included among the top collaborators of Dongze Lian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dongze Lian. Dongze Lian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 9 | |
| 4 | 8 | |
| 5 | 10 | |
| 6 | 2 | |
| 7 | 19 | |
| 8 | 9 | |
| 9 | 29 | |
| 10 | 76 | |
| 11 | 5 | |
| 12 | Towards Fast Adaptation of Neural Architectures with Meta Learning | 25 |
| 13 | 7 | |
| 14 | 166 | |
| 15 | 10 | |
| 16 | 137 | |
| 17 | 15 | |
| 18 | 24 | |
| 19 | Future Frame Prediction for Anomaly Detection - A New Baselinebreakdown → | 895 |
| 20 | 59 |
About Dongze Lian
Dongze Lian is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Artificial Intelligence, having authored 22 papers that have together received 1.6k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (9 papers), Multimodal Machine Learning Applications (7 papers) and Anomaly Detection Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (870 citations), Artificial Intelligence (1.3k citations) and Computer Networks and Communications (687 citations). Dongze Lian has collaborated with scholars based in China, Singapore and United Kingdom. Frequent co-authors include Shenghua Gao, Weixin Luo, Wen Liu, Lixin Duan, Jia Zheng, Jing Li, Jinhui Tang, Xi Peng, Binbin Huang and Lina Hu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and The Visual Computer.
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.