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Information × Registration Number 2123U011191, Article popup.category Препринт Title A deep learning-based pipeline for visual geolocation in the urban environment (AI translated) popup.author Tsapiv VolodymyrTsapiv Volodymyr popup.publication 01-01-2023 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/4428 popup.publisher Description The precise identification of location in urban areas is a challenging problem for Global Navigation Satellite Systems (GNSS), such as GPS, because of obstacles that include signal blockage, multipath interference, and urban canyons, among other factors. This thesis proposes a structure-based visual localization pipeline that uses a combination of Deep Neural Networks (DNNs) and traditional computer vision algorithms to perform accurate localization by an image. Additionally, we provide a collection of helpful tools for constructing a reference database for visual localization that can be used with any city found on Google Maps. The proposed method was evaluated on established visual localization benchmarks and produced competitive outcomes. popup.nrat_date 2025-11-05 Close