Drone detection and classification using deep leaning
| dc.contributor.author | BENHAFRI, MERIEM | |
| dc.contributor.author | CHARRIF, MERIEM | |
| dc.contributor.author | KHELDOUN, AHMED | |
| dc.date.accessioned | 2024-10-21T13:44:47Z | |
| dc.date.available | 2024-10-21T13:44:47Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | This document explores the application of deep learning models, specifically YOLOv5 and YOLOv8, for drone detection, with a focus on addressing the challenge of detecting small drones. Through rigorous experimentation and optimization of training parameters, our study aims to enhance the accuracy and efficiency of drone detection systems. The results demonstrate significant benefits, particularly in real-time performance and precision, crucial for enhancing security and surveillance capabilities in various environments. | fr_FR |
| dc.identifier.citation | Ingénierie des systèmes et technologie du web | fr_FR |
| dc.identifier.govdoc | M62496 | |
| dc.identifier.uri | https://dspace.univ-medea.dz/handle/123456789/12170 | |
| dc.language.iso | en | fr_FR |
| dc.relation.ispartofseries | M62496; | |
| dc.subject | drone detection | fr_FR |
| dc.subject | Deep learning | fr_FR |
| dc.subject | YOLOv5 | fr_FR |
| dc.subject | YOLOv8 | fr_FR |
| dc.subject | small drones | fr_FR |
| dc.title | Drone detection and classification using deep leaning | fr_FR |
| dc.type | Memoire | fr_FR |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- drone detection and classification using deep learning.pdf
- Size:
- 10.37 MB
- Format:
- Adobe Portable Document Format
- Description:
