Han-Jia Ye
About
In The Last Decade
Han-Jia Ye
51 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 778
- Radiology, Nuclear Medicine and Imaging 164
- Signal Processing 91
- Media Technology 83
Countries citing papers authored by Han-Jia Ye
This map shows the geographic impact of Han-Jia Ye'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 Han-Jia Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han-Jia Ye more than expected).
Fields of papers citing papers by Han-Jia Ye
This network shows the impact of papers produced by Han-Jia Ye. 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 Han-Jia Ye. The network helps show where Han-Jia Ye may publish in the future.
Co-authorship network of co-authors of Han-Jia Ye
This figure shows the co-authorship network connecting the top 25 collaborators of Han-Jia Ye. A scholar is included among the top collaborators of Han-Jia Ye 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 Han-Jia Ye. Han-Jia Ye 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 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | Class-Incremental Learning: A Survey breakdown → | 58 |
| 8 | 33 | |
| 9 | The Capacity and Robustness Trade-Off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecasting breakdown → | 63 |
| 10 | 2 | |
| 11 | 23 | |
| 12 | 16 | |
| 13 | A$^2$-Net: Learning Attribute-Aware Hash Codes for Large-Scale Fine-Grained Image Retrieval | 6 |
| 14 | 0 | |
| 15 | Learning Classifier Synthesis for Generalized Few-Shot Learning | 3 |
| 16 | Rectify Heterogeneous Models with Semantic Mapping | 13 |
| 17 | Learning Embedding Adaptation for Few-Shot Learning | 33 |
| 18 | Learning Feature Aware Metric | 2 |
| 19 | 12 | |
| 20 | Auxiliary information regularized machine for multiple modality feature learning | 11 |
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.