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Pattern recognition applications for image classification

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dc.contributor Graduate Program in Industrial Engineering.
dc.contributor.advisor Hörmann, Wolfgang.
dc.contributor.author Çetinkaya, Mert.
dc.date.accessioned 2023-03-16T10:30:08Z
dc.date.available 2023-03-16T10:30:08Z
dc.date.issued 2021.
dc.identifier.other IE 2021 C48
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/13445
dc.description.abstract Pattern recognition and image classification applications are the topic of this thesis. Its focus is on neural network based techniques, in other words, convolutional neural networks, and they are tried to be used in the most efficient way. In addition to convolutional neural networks, some experiments using more classical pattern recognition and classi cation techniques are conducted and their results are evaluated. The applications are made for traffic sign recognition and medical image recognition using different public datasets that were also preferred in previous studies. In the context of these applications, the obtained results are also compared to the results available in the literature. As an additional experiment, an optical character recognition and a real text digitalization method is also proposed as a proof of concept study. These experiments again consist of similar steps, but, also a character segmentation approach is developed on real text images, to extract the characters to be classiffied. During all these experiments, image processing and pattern recognition and classification techniques are used, and some proposal are brought to augment their efficiency.
dc.format.extent 30 cm.
dc.publisher Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021.
dc.subject.lcsh Machine learning.
dc.subject.lcsh Pattern perception.
dc.title Pattern recognition applications for image classification
dc.format.pages xvi, 110 leaves ;


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