عنوان

Derin öğrenme ile araç tipi sınıflandırma

شماره

TL58102

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Derin öğrenme ile araç tipi sınıflandırma

نام عام مواد

[Thesis]

نام نخستين پديدآور

Yaraş, Neriman

نام ساير پديدآوران

Özuysal, Mustafa

نام ناشر، پخش کننده و غيره

Izmir Institute of Technology (Turkey)

تاریخ نشرو بخش و غیره

2020

متن يادداشت

78 p.

جزئيات پايان نامه و نوع درجه آن

Master's

کسي که مدرک را اعطا کرده

Izmir Institute of Technology (Turkey)

امتياز متن

2020

متن يادداشت

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.

اصطلاح موضوعی

Artificial intelligence

اصطلاح موضوعی

Automation

اصطلاح موضوعی

Computer engineering

اصطلاح موضوعی

Datasets

اصطلاح موضوعی

Neural networks

مستند نام اشخاص تاييد نشده

Yaraş, Neriman

مستند نام اشخاص تاييد نشده

Özuysal, Mustafa

مستند نام تنالگان تاييد نشده

Izmir Institute of Technology (Turkey)

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y