|Project's title||Developing deep learning methods for application in document analysis and recognition|
|Research hosting institution||Institute of Information Technology|
|Project leader’s name||PhD. Nguyen Duc Dung|
|Project duration||01/01/2019 - 31/12/2021|
|Project’s budget||600 million VND|
|Goal and objectives of the project|| |
- Develop new text structure recognition algorithm, including physical structure (position) and logical structure (format) based on deep learning approaches and existing research results. The new algorithm focuses on minimizing the detection error and the error of discriminating/misidentifying the data blocks in the document text image page.
|Main results||Theoretical results: 01 Submit a scientific article in the journal International SCI / SCIE on methods to detect and analyze the structure of the table, locate the form, content identification and table form and 01 Scientidic article in conference proceedings with the International criticism or national workshop. |
Applied results: The program: document analysis and recognition.
|Novelty and actuality and scientific meaningfulness of the results|| |
We present TableSegNet, a compact architecture of a fully convolutional network to detect and separate tables simultaneously.
|Products of the project|| |
- Scientific papers in referred journals (list):
- Technological products (describe in details: technical characteristics, place):
|Images of project|| |