Identification of Vehicle Logos in Deep Learning: A Comprehensive Survey

The identification of vehicle logos in videos and images can be considered a crucial undertaking in several applications, such as traffic surveillance systems. The accelerated progress of deep learning has resulted in an increasing need within the computer vision field for the development of efficient, robust, and outstanding services across several domains, such as the recognition and classification of automobile emblems. This survey begins with an exploration of the escalating significance of logos and the associated challenges to their detection. The core problem addressed revolves around the necessity for robust methodologies capable of accurately identifying logos in diverse scenarios. The objective of our study is to conduct a comprehensive examination of existing deep learning strategies for logo detection, unveil their real-world applications, and contribute insights into future challenges and directions in this domain. Our survey uncovers valuable insights into publicly available datasets, showcasing their diversity and relevance in evaluating logo detection algorithms. An in-depth analysis of deep learning strategies follows, elucidating their strengths and limitations and providing a nuanced understanding of their performance metrics. The survey concludes by delineating anticipated challenges and proposing future directions, thereby presenting a roadmap for researchers and practitioners seeking to advance logo detection using deep learning techniques.