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https://dspace.ctu.edu.vn/jspui/handle/123456789/93995
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Nguyễn, Thái Nghe | - |
dc.contributor.author | Nguyễn, Thị Bich Huyền | - |
dc.date.accessioned | 2023-12-27T01:40:48Z | - |
dc.date.available | 2023-12-27T01:40:48Z | - |
dc.date.issued | 2023 | - |
dc.identifier.other | B1910648 | - |
dc.identifier.uri | https://dspace.ctu.edu.vn/jspui/handle/123456789/93995 | - |
dc.description | 55 Tr | vi_VN |
dc.description.abstract | In recent years, the use of machine learning has rapidly advanced in various fields, including computer vision, recommendation systems, image classification and recognition, and natural language processing, among others. This thesis provides an overview of machine learning and the knowledge of models and algorithms used in the topic. After explaining the necessary technological concepts, we describe the method for building a system for stranger detection. We discuss using algorithms and machine learning models for identifying strangers in videos. Furthermore, we address the approach of sending alerts through the Telegram application upon detecting strangers. Through the research and implementation of this thesis, it is expected to contribute to improving safety and security for individuals by detecting and alerting the presence of strangers. This will enable people to take appropriate protective measures. Additionally, this topic will provide a foundation for further research and development in this field, with increasing levels of depth and exploration. | vi_VN |
dc.language.iso | en | vi_VN |
dc.publisher | Trường Đại Học Cần Thơ | vi_VN |
dc.subject | CÔNG NGHỆ THÔNG TIN - CHẤT LƯỢNG CAO | vi_VN |
dc.title | TÊN TIẾNG ANH: STRANGER DETECTION SYSTEM. | vi_VN |
dc.title.alternative | HỆ THỐNG PHÁT HIỆN NGƯỜI LẠ | vi_VN |
dc.type | Thesis | vi_VN |
Appears in Collections: | Trường Công nghệ Thông tin & Truyền thông |
Files in This Item:
File | Description | Size | Format | |
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_file_ Restricted Access | 2.73 MB | Adobe PDF | ||
Your IP: 3.149.243.29 |
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