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" Derin öğrenme ile araç tipi sınıflandırma "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 1112201
Doc. No : TLpq2522625103
Main Entry : Özuysal, Mustafa
: Yaraş, Neriman
Title & Author : Derin öğrenme ile araç tipi sınıflandırma\ Yaraş, NerimanÖzuysal, Mustafa
College : Izmir Institute of Technology (Turkey)
Date : 2020
student score : 2020
Degree : Master's
Page No : 78
Abstract : 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.
Subject : Artificial intelligence
: Automation
: Computer engineering
: Datasets
: Neural networks
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