Paper Title: DEEP LEARNING IN COMPUTER VISION: FROM OBJECT DETECTION TO AUTOMOBILE VEHICLES
Author:
Abstract:
Deep learning has significantly advanced the field of computer vision, transforming how machines interpret visual data and enabling new applications such as autonomous vehicles. This article reviews the development of deep learning technologies, from early pattern recognition to sophisticated Convolutional Neural Networks (CNNs). It examines the role of deep learning in improving object detection accuracy and real-time performance, which is crucial for the safe operation of autonomous vehicles. The discussion addresses technical challenges including data scarcity, high computational costs, and the need for large-scale datasets. Ethical concerns such as privacy issues and potential bias in AI models are also explored. The article concludes by considering future directions, including advancements in deep learning models and their integration with other AI technologies. It highlights the potential for deep learning to revolutionize transportation and underscores the importance of collaboration between tech companies, automakers, and regulators to address the challenges and ensure the responsible deployment of autonomous vehicles.
Keywords:Deep Learning, Computer Vision, Object detection, Autonomous Vehicles
DOI Link – https://doi.org/10.63431/AIJITR/3.II.2026.100-109
Review By – Dr. Amit Adhikari and Prof. Dr. Shishir Kumar Bej