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" Numerical methods for diffusion phenomena in building physics : "
Nathan Mendes, Marx Chhay, Julien Berger, Denys Dutykh.
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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1112201
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| Doc. No
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TLpq2522625103
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| Main Entry
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Özuysal, Mustafa
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Yaraş, Neriman
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| Title & Author
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Derin öğrenme ile araç tipi sınıflandırma\ Yaraş, NerimanÖzuysal, Mustafa
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| College
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Izmir Institute of Technology (Turkey)
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| Date
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2020
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| student score
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2020
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| Degree
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Master's
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| Page No
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78
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| Abstract
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In this thesis, we studied the vehicle type classification problem from several perspectives. We apply a deep learning technique with different parameters such as image size and the number of images in data sets to the classification of an image as one of the nine vehicle types. After choosing the most appropriate one among trained models, we convert the problem into a hierarchical tree classification problem so that it could be analyzed in three different tree hierarchies. Experiments are performed using three computational methods for calculating possibilities for each of the nine classes that correspond to the leaves of the hierarchical trees. These studies result in a conclusion that 0.762812 average accuracy is obtained when traditional arithmetic mean computation applied on the hierarchical tree with level-2 using the Stanford Dataset by 224 image size on ResNet34 architecture.
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| Subject
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Artificial intelligence
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Automation
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Computer engineering
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Datasets
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Neural networks
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