Yicong Hong
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Aerospace Engineering
- Control and Systems Engineering
- Information Systems
- Co-authors
- Qi WuStephen Jay GouldYuankai QiCristian Rodríguez-OpazoPeng WangZun WangYu ZhengMing–Hsuan Yang
- Topics
- Multimodal Machine Learning Applications (9 papers)Advanced Image and Video Retrieval Techniques (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)2021 IEEE/CVF International Conference on Computer Vision (ICCV)
- Partner nations
- AustraliaUnited StatesChina
In The Last Decade
Yicong Hong
12 papers receiving 488 citations
Hit Papers
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 413
- Artificial Intelligence 291
- Aerospace Engineering 55
- Control and Systems Engineering 35
- Information Systems 15
Countries citing papers authored by Yicong Hong
This map shows the geographic impact of Yicong Hong'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 Yicong Hong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yicong Hong more than expected).
Fields of papers citing papers by Yicong Hong
This network shows the impact of papers produced by Yicong Hong. 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 Yicong Hong. The network helps show where Yicong Hong may publish in the future.
Co-authorship network of co-authors of Yicong Hong
This figure shows the co-authorship network connecting the top 25 collaborators of Yicong Hong. A scholar is included among the top collaborators of Yicong Hong 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 Yicong Hong. Yicong Hong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 14 | |
| 3 | NavGPT: Explicit Reasoning in Vision-and-Language Navigation with Large Language Modelsbreakdown → | 62 |
| 4 | 24 | |
| 5 | 35 | |
| 6 | 9 | |
| 7 | 22 | |
| 8 | 43 | |
| 9 | 54 | |
| 10 | 48 | |
| 11 | 143 | |
| 12 | 31 |
About Yicong Hong
Yicong Hong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 12 papers that have together received 494 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (413 citations), Artificial Intelligence (291 citations) and Aerospace Engineering (55 citations). Yicong Hong has collaborated with scholars based in Australia, United States and China. Frequent co-authors include Qi Wu, Stephen Jay Gould, Yuankai Qi, Cristian Rodríguez-Opazo, Qi Wu, Peng Wang, Zun Wang, Yu Zheng, Ming–Hsuan Yang and Zizheng Pan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
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.