VGU RESEARCH REPOSITORY
Please use this identifier to cite or link to this item:
https://epub.vgu.edu.vn/handle/dlibvgu/1080
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Luc Duc Khoi | en_US |
dc.date.accessioned | 2021-04-16T04:38:39Z | - |
dc.date.available | 2021-04-16T04:38:39Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://epub.vgu.edu.vn/handle/dlibvgu/1080 | - |
dc.description.abstract | Nowadays, with a dramatic rise in technology and science, many applications have been developed and created remarkable changes in the life of everyone. Looking at Viet Nam, a beingdeveloped country where huge advantages in the labor force and investment takes place, the manufacturing and production field has become a key direction of the country’s economy developing plan. Therefore, the urgent need for technology is essential. One of the biggest problems is the quality of the product, which plays a crucial role in the success of a company. One of the solutions for this problem is a system to monitor, detect, and classify defects of goods. With the advancement in the machine learning field, simple to a complex task can be solved, and this results in a significant improvement in quality, cost, efficiency, and productivity. With a desire to learn and create a system of detection using machine learning, I choose “Machine Learning Techniques for Information Extraction to improve Production Control” topic for the thesis | en_US |
dc.language.iso | en | en_US |
dc.subject | Machine learning methods | en_US |
dc.subject | Information extraction | en_US |
dc.subject | Production control | en_US |
dc.title | Machine learning techniques for information extraction to improve production control | en_US |
dc.type | Thesis | en_US |
item.grantfulltext | restricted | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | other | - |
Appears in Collections: | Mechanical Engineering (MEN) |
Files in This Item:
File | Description | Size | Format | Existing users please Login |
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Machine learning techniques for information extraction to improve production control.pdf | 4.34 MB | Adobe PDF |
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