Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments

Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Manylion Llyfryddiaeth
Prif Awduron:	Mahmud, Ishtiaque, Ritu, Sumaia Arefin, Mahmood, Zaki Zawad
Awduron Eraill:	Chakrabarty, Amitabha
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2024
Pynciau:	YOLOv8 YOLOv5 Automated vehicles YOLOv7 Obstacle detection Navigational intelligence Traffic safety > Bangladesh. Computer vision. Traffic engineering. Automotive engineering.
Mynediad Ar-lein:	http://hdl.handle.net/10361/24349

Eitemau Tebyg

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A novel approach to forecast traffic congestion using CMTF and machine learning
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Automatic waste classification using deep learning and computer vision techniques
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An efficient algorithm for detecting traffic congestion and a framework for smart traffic control system
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Deep learning-based real-time pothole detection for avoiding road accident
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Reducing traffic congestion through ride sharing in Bangladesh: a case study of Dhaka City
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Four way effective traffic management system
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Document template identification and data extraction using machine learning and deep learning approach
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Crowed source based traffic analysis using machine learning algorithm
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