U
Umut Özkaya
Researcher at Selçuk University
Publications - 36
Citations - 882
Umut Özkaya is an academic researcher from Selçuk University. The author has contributed to research in topics: Support vector machine & Feature extraction. The author has an hindex of 10, co-authored 34 publications receiving 413 citations.
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Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
TL;DR: Early phase detection of Coronavirus (COVID-19), which is named by World Health Organization (WHO), by machine learning methods was implemented on abdominal Computed Tomography (CT) images to increase the classification performance.
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Coronavirus (COVID-19) Classification using Deep Features Fusion and Ranking Technique
TL;DR: This study provides an automated and highly effective method for detecting COVID-19 at an early stage using the convolutional neural network (CNN) architecture, which is the most successful image processing tool of today.
Journal ArticleDOI
Classification of Coronavirus (COVID-19) from X-ray and CT images using shrunken features.
TL;DR: The proposed machine learning method for the detection of viral epidemics by analyzing X‐ray and CT images has leveraging performance, especially to make the diagnosis of COVID‐19 in a short time and effectively.
Journal ArticleDOI
Skin Lesion Segmentation with Improved Convolutional Neural Network.
Şaban Öztürk,Umut Özkaya +1 more
TL;DR: The proposed improved FCN (iFCN) architecture is used for the segmentation of full-resolution skin lesion images without any pre- or post-processing to support the residual structure of the FCN architecture with spatial information.
Book ChapterDOI
Coronavirus (COVID-19) Classification Using Deep Features Fusion and Ranking Technique
TL;DR: In this article, the authors presented an automated and highly effective method for detecting COVID-19 at an early stage CT image features are extracted using the convolutional neural network (CNN) architecture, which is the most successful image processing tool of today.