Object Detection For Quadrotor Using Deep Learning
| dc.contributor.author | ISSAME, MAHDJOUBI | |
| dc.contributor.author | Enca/ A., BENYOUNES | |
| dc.date.accessioned | 2022-07-20T09:42:51Z | |
| dc.date.available | 2022-07-20T09:42:51Z | |
| dc.date.issued | 2022-07-20 | |
| dc.description.abstract | In this work, a type of unmanned aerial vehicle (UAV) called quadrotor with an object detection system is the subject that we will talk about. The main objectives of our work is the detection of chosen objects from the quadrotor. For that, there are two parts presented, the first one, a detailed description of the mathematical effects that applied to the structure of our system and how we implemented our system with showing all the parts, add to this we built it using simulink with the PID and we showed the results. In the second part, we will talk about artificial intelligence generally and deep learning specifically and we will show how exactly the detection happen using the right technics and algorithms with Yolov5 and which version we will use. Finally we will make a real test with the real time showing our prototype working in the field. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/30815 | |
| dc.language.iso | en | en_US |
| dc.publisher | university of M'sila | en_US |
| dc.subject | UAV, Object Detection, Quadrotor, Deep Learning, YOLO. | en_US |
| dc.title | Object Detection For Quadrotor Using Deep Learning | en_US |
| dc.type | Thesis | en_US |
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