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Detection of parking space availability based on video
 Kužela, Miloslav ; Frýza, Tomáš
This paper deals with the use of Machine vision and ML (Machine Learning) for a parking lot occupation detection. It presents and compares an already existing technology that solves such a problem with an AI (Artificial Intelligence) usecase. It introduces tools used to train and create such models and their subsequent results as well as a dataset that was used to verify the trained networks and discusses the future of how such a technology could be used to effectively and more affordably detect occupied parking spaces on parking lots.
Úplný záznam
Detection of parking space availability based on video
 Kužela, Miloslav ; Zelený, Ondřej (oponent) ; Frýza, Tomáš (vedoucí práce)
Determining a parking space occupation is often solved by using physical sensors located near a parking space, but with the rise of machine learning, it is possible to apply such technology with the use of cameras and detection algorithms to solve such a problem. This thesis focuses on the use of this machine learning model. Presents currently available models and detectors, discusses the creation of a custom data set with a custom file structure, trains such a model, and consults its results based on its accuracy when applied in a parking lot. This model is then used among side a created web server that allows the users of the parking lot to view the current occupancy and history. All by using the Python programming language with Torchvision libraries.
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