Enhancing Object Detection in Autonomous Cars: A Fusion of YOLO and Cascade R-CNN

Deshpande, Kalyani (2023) Enhancing Object Detection in Autonomous Cars: A Fusion of YOLO and Cascade R-CNN. Masters thesis, Dublin, National College of Ireland.

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Abstract

This study presents a novel hybrid implementation of an object detection system based on the YoloV4 and Cascade RCNN models. The research aims to understand the performance dynamics of these models in terms of precision, recall, Average Precision (AP), and mean Average Precision (mAP). During the comparison test, the YoloV4 model did pretty well, showing that it could handle high recall situations but had trouble keeping its precision steady. Its AP and mAP were both 0.16. It was easier for the Cascade RCNN Standalone model to keep its precision across a wider range of thresholds, as shown by its AP and mAP scores of 0.625. It was the YoloV4-Cascade RCNN hybrid model that did the best, with the highest scores (AP and mAP of 0.79) and a great balance between accuracy and recall. Combining different object detection methods to improve overall detection accuracy works, as shown by this hybrid model’s excellent performance. Understanding the study’s results is important for making progress in real-world applications like self-driving cars.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Anant, Aaloka UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TL Motor vehicles. Aeronautics. Astronautics Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence > Computer vision Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence > Computer vision H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Motor Industry
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	07 May 2025 14:13
Last Modified:	07 May 2025 14:13
URI:	https://norma.ncirl.ie/id/eprint/7507

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