Tao Kong
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Aerospace Engineering top 5%
- Media Technology top 1%
- Control and Systems Engineering top 5%
- Topics
- Advanced Neural Network Applications (13 papers)Multimodal Machine Learning Applications (11 papers)Advanced Image and Video Retrieval Techniques (11 papers)
In The Last Decade
Tao Kong
59 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Computer Vision and Pattern Recognition 2.1k
- Artificial Intelligence 802
- Aerospace Engineering 354
- Media Technology 326
- Control and Systems Engineering 292
Countries citing papers authored by Tao Kong
This map shows the geographic impact of Tao Kong'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 Tao Kong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tao Kong more than expected).
Fields of papers citing papers by Tao Kong
This network shows the impact of papers produced by Tao Kong. 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 Tao Kong. The network helps show where Tao Kong may publish in the future.
Co-authorship network of co-authors of Tao Kong
This figure shows the co-authorship network connecting the top 25 collaborators of Tao Kong. A scholar is included among the top collaborators of Tao Kong 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 Tao Kong. Tao Kong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 17 | |
| 4 | 2 | |
| 5 | 16 | |
| 6 | 53 | |
| 7 | 3 | |
| 8 | 12 | |
| 9 | 19 | |
| 10 | 20 | |
| 11 | Sparse R-CNN: End-to-End Object Detection with Learnable Proposalsbreakdown → | 933 |
| 12 | SOLOv2: Dynamic and Fast Instance Segmentation | 25 |
| 13 | SOLOv2: Dynamic, Faster and Stronger. | 56 |
| 14 | 1 | |
| 15 | 53 | |
| 16 | HyperNet: Towards Accurate Region Proposal Generation and Joint Object Detectionbreakdown → | 602 |
| 17 | 8 | |
| 18 | Multiobjective Group-Based Signal Optimization Model for Mixed Traffic Flows at Isolated Intersections | 0 |
| 19 | 12 | |
| 20 | 1 |
About Tao Kong
Tao Kong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Human-Computer Interaction, having authored 62 papers that have together received 3.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (13 papers), Multimodal Machine Learning Applications (11 papers) and Advanced Image and Video Retrieval Techniques (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Media Technology (326 citations) and Artificial Intelligence (802 citations). Tao Kong has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Rufeng Zhang, Fuchun Sun, Anbang Yao, Yurong Chen, Lei Li, Xinlong Wang, Chunhua Shen, Wei Zhan, Zehuan Yuan and Ping Luo. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Langmuir and IEEE Transactions on Image Processing.
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.