Occluded object detection for autonomous vehicles employing YOLOv5, YOLOX and Faster R-CNN

Occluded object detection for autonomous vehicles employing YOLOv5, YOLOX and Faster R-CNN

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Bibliografiska uppgifter
Huvudupphovsmän: Mostafa, Tanzim, Chowdhury, Sartaj Jamal
Övriga upphovsmän: Rhaman, Dr. Md. Khalilur
Materialtyp: Lärdomsprov
Språk:en_US
Publicerad: Brac University 2022
Ämnen:
Autonomous Vehicles
Occluded Object Detection
Object Detection
Machine Learning
Deep Learning
Supervised Learning
Occluded Objects Dataset
Transfer Learning
YOLOv5
YOLOX
Faster R-CNN
Cognitive learning theory (Deep learning)
Artificial intelligence
Machine learning
Autonomous vehicles
Automobiles
Länkar:http://hdl.handle.net/10361/17614

Internet

http://hdl.handle.net/10361/17614

Liknande verk