De‐Chuan Zhan
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Radiology, Nuclear Medicine and Imaging top 10%
- Information Systems top 5%
- Signal Processing top 5%
- Co-authors
- Han-Jia YeDa-Wei ZhouHexiang HuFei ShaZhi‐Hua ZhouYuan JiangYang YangXinchun Li
- Topics
- Domain Adaptation and Few-Shot Learning (40 papers)Multimodal Machine Learning Applications (25 papers)Advanced Image and Video Retrieval Techniques (18 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern RecognitionAdvanced Science
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
De‐Chuan Zhan
93 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Artificial Intelligence 1.7k
- Computer Vision and Pattern Recognition 1.0k
- Radiology, Nuclear Medicine and Imaging 184
- Information Systems 156
- Signal Processing 151
Countries citing papers authored by De‐Chuan Zhan
This map shows the geographic impact of De‐Chuan Zhan'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 De‐Chuan Zhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De‐Chuan Zhan more than expected).
Fields of papers citing papers by De‐Chuan Zhan
This network shows the impact of papers produced by De‐Chuan Zhan. 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 De‐Chuan Zhan. The network helps show where De‐Chuan Zhan may publish in the future.
Co-authorship network of co-authors of De‐Chuan Zhan
This figure shows the co-authorship network connecting the top 25 collaborators of De‐Chuan Zhan. A scholar is included among the top collaborators of De‐Chuan Zhan 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 De‐Chuan Zhan. De‐Chuan Zhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 8 | |
| 3 | 18 | |
| 4 | Class-Incremental Learning: A Surveybreakdown → | 58 |
| 5 | 33 | |
| 6 | The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecastingbreakdown → | 63 |
| 7 | 2 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 22 | |
| 11 | 16 | |
| 12 | Learning Classifier Synthesis for Generalized Few-Shot Learning | 3 |
| 13 | Rectify Heterogeneous Models with Semantic Mapping | 13 |
| 14 | Learning Embedding Adaptation for Few-Shot Learning | 33 |
| 15 | Instance Specific Discriminative Modal Pursuit: A Serialized Approach. | 2 |
| 16 | Learning Feature Aware Metric | 2 |
| 17 | Learning by actively querying strong modal features | 2 |
| 18 | Auxiliary information regularized machine for multiple modality feature learning | 11 |
| 19 | Multi-modal image annotation with multi-instance multi-label LDA | 47 |
| 20 | Semi-supervised learning with very few labeled training examples | 91 |
About De‐Chuan Zhan
De‐Chuan Zhan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research, having authored 103 papers that have together received 2.2k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (40 papers), Multimodal Machine Learning Applications (25 papers) and Advanced Image and Video Retrieval Techniques (18 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Computer Vision and Pattern Recognition (1.0k citations) and Signal Processing (151 citations). De‐Chuan Zhan has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Han-Jia Ye, Da-Wei Zhou, Hexiang Hu, Fei Sha, Zhi‐Hua Zhou, Yuan Jiang, Yang Yang, Xinchun Li, Liang Ma and Shiliang Pu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and Advanced Science.
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.