Win Pa Pa
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing
- Language and Linguistics
- Information Systems
- Co-authors
- Ye Kyaw ThuEiichiro SumitaChenchen DingAndrew FinchMasao UtiyamaToshiaki NakazawaRaj DabreAnoop Kunchukuttan
- Topics
- Natural Language Processing Techniques (27 papers)Topic Modeling (21 papers)Speech Recognition and Synthesis (20 papers)
- Journals
- SHILAP Revista de lepidopterologíaLanguage Resources and EvaluationInternational Journal of Electrical and Computer Engineering (IJECE)
In The Last Decade
Win Pa Pa
31 papers receiving 201 citations
Peers
Comparison fields: 5 of 22
- Artificial Intelligence 208
- Computer Vision and Pattern Recognition 74
- Signal Processing 19
- Language and Linguistics 19
- Information Systems 8
Countries citing papers authored by Win Pa Pa
This map shows the geographic impact of Win Pa Pa'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 Win Pa Pa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Win Pa Pa more than expected).
Fields of papers citing papers by Win Pa Pa
This network shows the impact of papers produced by Win Pa Pa. 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 Win Pa Pa. The network helps show where Win Pa Pa may publish in the future.
Co-authorship network of co-authors of Win Pa Pa
This figure shows the co-authorship network connecting the top 25 collaborators of Win Pa Pa. A scholar is included among the top collaborators of Win Pa Pa 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 Win Pa Pa. Win Pa Pa 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 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | Automatic Myanmar Image Captioning using CNN and LSTM-Based Language Model | 12 |
| 10 | 14 | |
| 11 | 4 | |
| 12 | 4 | |
| 13 | 19 | |
| 14 | 5 | |
| 15 | UCSYNLP-Lab Machine Translation Systems for WAT 2018. | 2 |
| 16 | 0 | |
| 17 | Introducing the Asian Language Treebank (ALT). | 20 |
| 18 | Comparison of Grapheme-to-Phoneme Conversion Methods on a Myanmar Pronunciation Dictionary. | 12 |
| 19 | 16 | |
| 20 | 8 |
About Win Pa Pa
Win Pa Pa is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition, having authored 39 papers that have together received 228 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (27 papers), Topic Modeling (21 papers) and Speech Recognition and Synthesis (20 papers). The work is most often cited by research in Artificial Intelligence (208 citations), Computer Vision and Pattern Recognition (74 citations) and Language and Linguistics (19 citations). Win Pa Pa has collaborated with scholars based in Myanmar, Japan and Thailand. Frequent co-authors include Ye Kyaw Thu, Eiichiro Sumita, Chenchen Ding, Andrew Finch, Masao Utiyama, Toshiaki Nakazawa, Raj Dabre, Anoop Kunchukuttan, Isao Goto and Sadao Kurohashi. Their work appears in journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and International Journal of Electrical and Computer Engineering (IJECE).
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.