 Enhancing Transportation Systems through Applied Deep Learning Algorithms THESIS TOPIC PROPOSAL Institute: Budapest University of Technology and Economics computer sciences Doctoral School of Informatics Thesis supervisor: Bence Kővári Location of studies (in Hungarian): Department of Automation and Applied Informatics Abbreviation of location of studies: AUT Description of the research topic: This proposed doctoral research seeks to elevate the realms of transportation infrastructure through the strategic integration of cutting-edge deep learning algorithms, specifically tailored for real-time traffic monitoring and bridge weight-in-motion systems. In the contemporary landscape of urbanization and technological advancement, the optimization of traffic management and the structural health monitoring of critical infrastructure such as bridges demand innovative solutions. This study aims to address these challenges by harnessing the potential of deep learning methodologies, thereby contributing to enhanced accuracy, efficiency, and adaptability in transportation systems. Required language skills: English Number of students who can be accepted: 2 Deadline for application: 2024-06-19 |