Chenlei Guo
- Computer Vision and Pattern Recognition top 0.5%
- Sensory Systems top 1%
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 10%
- Media Technology top 2%
- Topics
- Topic Modeling (16 papers)Speech and dialogue systems (9 papers)Natural Language Processing Techniques (9 papers)
- Journals
- IEEE Transactions on Image ProcessingIEEE Transactions on Biomedical EngineeringAI Magazine
- Partner nations
- United StatesGermanyChina
In The Last Decade
Chenlei Guo
24 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 1.2k
- Sensory Systems 309
- Artificial Intelligence 225
- Cognitive Neuroscience 215
- Media Technology 157
Countries citing papers authored by Chenlei Guo
This map shows the geographic impact of Chenlei Guo'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 Chenlei Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenlei Guo more than expected).
Fields of papers citing papers by Chenlei Guo
This network shows the impact of papers produced by Chenlei Guo. 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 Chenlei Guo. The network helps show where Chenlei Guo may publish in the future.
Co-authorship network of co-authors of Chenlei Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Chenlei Guo. A scholar is included among the top collaborators of Chenlei Guo 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 Chenlei Guo. Chenlei Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 10 | |
| 8 | 0 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 12 | |
| 12 | 4 | |
| 13 | 6 | |
| 14 | IQ-Net: A DNN Model for Estimating Interaction-level Dialogue Quality with Conversational Agents. | 3 |
| 15 | 18 | |
| 16 | Deep Learning Powered In-Session Contextual Ranking using Clickthrough Data | 19 |
| 17 | 6 | |
| 18 | 26 | |
| 19 | A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compressionbreakdown → | 690 |
| 20 | Spatio-temporal Saliency detection using phase spectrum of quaternion fourier transformbreakdown → | 521 |
About Chenlei Guo
Chenlei Guo is a scholar working on Artificial Intelligence, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 1.5k indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Speech and dialogue systems (9 papers) and Natural Language Processing Techniques (9 papers). The work is most often cited by research in Sensory Systems (309 citations), Computer Vision and Pattern Recognition (1.2k citations) and Human-Computer Interaction (134 citations). Chenlei Guo has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Liming Zhang, Qi Ma, Xing Fan, Benjamin Yao, Ling Yuan, Gustavo Aguilar, Yu Zhang, Ruhi Sarikaya, Saurabh Gupta and Xiujun Li. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Biomedical Engineering and AI Magazine.
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.