مشروع البحث: Machine Learning-Based Solution For Automatic Border Surveillance System
| dc.contributor.advisor | Dr. Teresa Riesgo Alcaide | |
| dc.contributor.advisor | Dr. José Manuel Lanza Gutiérrez | |
| dc.date.accessioned | 2026-06-02T09:50:05Z | |
| dc.date.available | 2026-06-02T09:50:05Z | |
| dc.description | AI is specifically associated with ML techniques. This is a common understanding in contemporary AI discussions. ML is a subset of AI that focuses on developing algorithms and models that enable computers to learn patterns and make decisions without being explicitly programmed based on data.( | |
| dc.description.abstract | autonomous BSS using cutting-edge technologies such as Machine Learning (ML) and AI is the focus of the doctoral thesis, whose main aim is to address the challenges of surveillance in complex environments like the Sahara desert by embedding ML methods for vision-based applications in fixed Long wave infrared (LWIR) cameras to detect intruders. These LWIR cameras work within the edge computing to shift computation tasks from the cloud to the edge, resulting in a real-time BSS with high accuracy and low latency. The term "AI" or "Artificial Intelligence" has indeed evolved over time and now has become a broad and encompassing field that covers various techniques and approaches. Originally, AI was associated with symbolic methods, such as formal logic and ontologies. However, as technology advanced, the scope of AI expanded to include statistical methods like ML, data mining, and probabilistic models | |
| dc.identifier | 1230 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/2138 | |
| dc.subject | Learning-Based Solution For Automatic Border | |
| dc.title | Machine Learning-Based Solution For Automatic Border Surveillance System | |
| dspace.entity.type | Project | |
| project.endDate | 2024 | |
| project.funder.name | هندسة اتصالات | |
| project.investigator | خليفة البلوزي | |
| project.startDate | 2023 |