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.

Bibliographische Detailangaben
Hauptverfasser:	Mostafa, Tanzim, Chowdhury, Sartaj Jamal
Weitere Verfasser:	Rhaman, Dr. Md. Khalilur
Format:	Abschlussarbeit
Sprache:	en_US
Veröffentlicht:	Brac University 2022
Schlagworte:	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
Online Zugang:	http://hdl.handle.net/10361/17614

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