SMART OBJECT DETECTION FOR AUTONOMOUS VEHICLES
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Abstract
A smart object detection system receives development with the purpose of supporting autonomous vehicles through improved safety mechanisms and decision-making capabilities. Real- time operation and accurate vehicle classification with high confidence rates make this system possible through its deep learning-based object detection model which received training from KITTI dataset data. The voice navigation module produces reactive commands such as “Obstacle on left, turn right” through its spatial awareness capabilities to enable responsive guidance. Through its testing the model operates effectively under different lighting conditions while maintaining performance in complex road environments. YOLOv8 demonstrated better detection efficiency through its evaluation of YOLO architectures for detection efficiency.
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