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Hyperspectral images offer a good separability among land cover classes, owing to their advantages to provide spectral bands with narrow wavelength intervals. It is also possible to further increase classification accuracy of hyperspectral images by integrat…

Brain tumor is a progressive disease that significantly affects human life. These diseases can reduce the quality of life by causing losses in motor and cognitive functions. Since the chance of treatment decreases when not diagnosed early, advanced technologie…

Over the years, developments in the world of science and technology have emerged. Developments in image classification methods can also be evaluated in this context. Nowadays, the use of image classification methods for extracting information from data obtaine…

In this study, a classification problem is discussed to predict whether individuals' annual income levels are above $50,000. The UCI Adult Income Dataset, which is derived from the 1994 US Census (Census) data and is widely used in the field of machine learnin…

The incidence of skin cancer is increasing. Early detection of cases of skin cancer is vital for treatment. Recently, computerized methods have been widely used in cancer diagnosis. These methods have important advantages such as no human error, short diagnosi…

Word embedings are intense vector representations of words. They capture the semantic order between words. In our study, we propose a new method for classifying text by author, using word embeds and author vector space. Using each author's books, we trained th…

3D object classification has been widely studied in robotic community in recent years. According to types of features that are utilized to describe an object, 3D object classification studies can be separated into two main categories (local and global).The loc…

Early detection of lung cancer remains a critical challenge in medical imaging, where accurate classification between benign and malignant pulmonary nodules can significantly impact patient outcomes. This study presents a comprehensive comparative analysis of …

Elektromiyografi, kas aktivitesi sonucunda meydana gelen biyolojik işaretlerin ölçülmesine olanak sağlayan invaziv olmayan bir yöntemidir. Yüzey ve iğne elektromiyografisi olarak uygulama amacına göre iki şekilde kullanılmaktadır.  Bu çalışmada internet üzerin…

Deep learning is a machine learning sub-field that uses deep neural networks. Instead of customized algorithms for each study in this field, it is aimed to cover the wider data set of solutions based on learning the data. Deep learning is a promising approach …

Neural Network has been used in a number of scientific fields including medical diagnosis. It is clear that classification is one of the main challenges in any medical diagnosis. However, the drawbacks of conventional neural network classifier are summarized a…

It is important to determine the initial level of failures of induction motors used in many industrial applications. The sudden stops of the system can be prevented with the pre-detection of the fault. The experiment mechanism was established to detect mechani…

Eğitim sektörünün giderek büyüyen yapısında, yükseköğretim kurumları, öğrenci performansının akademik olarak iyileştirilmesi ve öğrencilerin okulu bırakmalarını önlemek için veri madenciliği araçlarını ve tekniklerini kullanmaktadır. Veriler sosyo-ekonomik, de…

Teknolojinin ilerlemesi ile birlikte birçok veri dijital ortamlarda kayıt altına alınarak büyük veri yığınları ortaya çıkmıştır. Veri madenciliği sayesinde bu büyük veri yığınlarının içinden anlamlı ve yararlı bilgilerin ortaya çıkarılması için çalışmalar yapı…

Text mining, which aims to derive unknown and useful information from available textual data, is one of the subfield of data mining. Text mining transforms unstructured textual data into structured form by utilizing various methods. Data mining techniques ca…

Robust object detection and classification in dynamic industrial scenarios is still a challenge, in particular if the system has to work in real-time on mid-ranged hardware. Classical vision-based methods have difficulties to cope with low/weak illumination, r…

Bu çalışmada UCI Makine Öğrenmesi havuzundan alınan kardiotokogram verisinde morfolojik örüntü sınıflandırması yapılmıştır. Sınıflandırıcı olarak kompleks değerli yapay sinir ağları kullanılmıştır. Sınıflandırıcının performansı 10-katlı çapraz doğrulama yaklaş…

Detecting objects meaningfully and correctly have been challenged problem for years. Several algorithms and techniques have been developed for the extraction of man-made objects from high resolution remote sensing imagery. This paper describes and comparison t…

Multiple Birth Support Vector Machines (MB-SVM) were introduced as a powerful extension of SVM. Although the basic idea is like SVM, optimal non-parallel hyperplanes are used for each class category. One may find different implementations of this approach in t…

In the last decade, deep learning in general and Convolutional Neural Networks (CNN) have achieved a human level and outstanding performance in almost all computer-based systems such as classification(text, images, and videos). Building an efficient CNN archit…