Guanglai Gao
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Computational Mechanics
- Experimental and Cognitive Psychology
- Co-authors
- Rui LiuFeilong BaoHaizhou LiBerrak ŞişmanXueliang ZhangHui ZhangXiangdong SuWeihua Wang
- Topics
- Natural Language Processing Techniques (36 papers)Speech Recognition and Synthesis (35 papers)Topic Modeling (25 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessNeurocomputing
In The Last Decade
Guanglai Gao
99 papers receiving 663 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 468
- Computer Vision and Pattern Recognition 275
- Signal Processing 233
- Computational Mechanics 47
- Experimental and Cognitive Psychology 40
Countries citing papers authored by Guanglai Gao
This map shows the geographic impact of Guanglai Gao'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 Guanglai Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guanglai Gao more than expected).
Fields of papers citing papers by Guanglai Gao
This network shows the impact of papers produced by Guanglai Gao. 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 Guanglai Gao. The network helps show where Guanglai Gao may publish in the future.
Co-authorship network of co-authors of Guanglai Gao
This figure shows the co-authorship network connecting the top 25 collaborators of Guanglai Gao. A scholar is included among the top collaborators of Guanglai Gao 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 Guanglai Gao. Guanglai Gao 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 | 0 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | Robust Speech Dereverberation Based on WPE and Deep Learning | 1 |
| 13 | 1 | |
| 14 | A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction | 2 |
| 15 | Mongolian Named Entity Recognition System with Rich Features | 4 |
| 16 | Missing feature reconstruction methods for robust speaker identification | 2 |
| 17 | 10 | |
| 18 | A Skew Detection Method of Mongolian Document Images | 1 |
| 19 | A Method of Layout Analysis for Mongolian Document Images Based on Connected Components | 1 |
| 20 | Feature Selection of Mongolian Characters in the Recognition of Printed Mongolian Characters | 0 |
About Guanglai Gao
Guanglai Gao is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 109 papers that have together received 715 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (36 papers), Speech Recognition and Synthesis (35 papers) and Topic Modeling (25 papers). The work is most often cited by research in Signal Processing (233 citations), Artificial Intelligence (468 citations) and Computer Vision and Pattern Recognition (275 citations). Guanglai Gao has collaborated with scholars based in China, Singapore and Mongolia. Frequent co-authors include Rui Liu, Feilong Bao, Haizhou Li, Berrak Şişman, Xueliang Zhang, Hui Zhang, Xiangdong Su, Hui Zhang, Weihua Wang and Jingdong Li. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Neurocomputing.
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.