Pei Guo
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Materials Chemistry
- Artificial Intelligence
- Media Technology top 10%
- Co-authors
- Jun SangHong XiangZhongyuan WuHaibo HuQian ZhangBin CaiRuijin LiaoJianwu Wang
- Topics
- High voltage insulation and dielectric phenomena (5 papers)Power Transformer Diagnostics and Insulation (5 papers)Bayesian Modeling and Causal Inference (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaSensorsINTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Pei Guo
25 papers receiving 358 citations
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 145
- Electrical and Electronic Engineering 99
- Materials Chemistry 75
- Artificial Intelligence 70
- Media Technology 47
Countries citing papers authored by Pei Guo
This map shows the geographic impact of Pei 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 Pei Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei Guo more than expected).
Fields of papers citing papers by Pei Guo
This network shows the impact of papers produced by Pei 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 Pei Guo. The network helps show where Pei Guo may publish in the future.
Co-authorship network of co-authors of Pei Guo
This figure shows the co-authorship network connecting the top 25 collaborators of Pei Guo. A scholar is included among the top collaborators of Pei 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 Pei Guo. Pei 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 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 6 | |
| 8 | 14 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 22 | |
| 12 | 7 | |
| 13 | 3 | |
| 14 | Neural Network Interpretation via Fine Grained Textual Summarization. | 4 |
| 15 | Fine-grained Visual Categorization using PAIRS: Pose and Appearance Integration for Recognizing Subcategories. | 4 |
| 16 | 29 | |
| 17 | 156 | |
| 18 | 1 | |
| 19 | 50 | |
| 20 | 1 |
About Pei Guo
Pei Guo is a scholar working on Energy Engineering and Power Technology, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 30 papers that have together received 380 indexed citations. Recurring topics across this work include High voltage insulation and dielectric phenomena (5 papers), Power Transformer Diagnostics and Insulation (5 papers) and Bayesian Modeling and Causal Inference (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (145 citations), Media Technology (47 citations) and Automotive Engineering (45 citations). Pei Guo has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jun Sang, Hong Xiang, Zhongyuan Wu, Haibo Hu, Qian Zhang, Bin Cai, Ruijin Liao, Jianwu Wang, Haibin Liu and Yuandi Lin. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY.
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.