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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…

Eşikleme yöntemleri kenar belirleme, bölütleme ve kümeleme yaklaşımlarında sıklıkla kullanılmaktadır. Söz konusu teknikler yardımıyla renk kanallarından çeşitli sayıda kümeler elde edilebilir. Ancak, hangi yaklaşımın daha başarılı olduğu konusu belirsizliğini …

Pansharpening, which is transferring the spatial content of a high-resolution panchromatic (PAN) band into a lowerresolution multispectral (MS) image to produce a spatially enhanced MS image, has always been one of the hottest topics of image processing. Nume…

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…

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 …

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…

The use of GPUs for general purpose applications is not a recent approach, but it was quickly becoming widespread with NVIDIA's CUDA (Compute Unified Device Architecture) architecture based on C programming language in 2007. Algorithms suitable for parallel op…

Image processing methods have been widely used for detection of product faults in recent years. Images of industrial products that made of various materials are taken with different types of cameras and by using different lenses. Working on images of metallic …

In recent years, computer vision has taken great strides in understanding and recognition the visual scenes together with deep learning technologies. Object recognition is one of the key areas of the computer vision applications. It is mainly concerned with re…

In today's increasingly competitive environment, cities like businesses need to strengthen their image. Cities with a strong brand image attract attention by providing a distinctive feature. In the development of the cities, the images that contribute to the d…

In this study, the elimination of zero diffraction order and twin image from three dimensional reconstructed images in digital holography and the image enhancement are desired to achieve in a short time by using hybrid methods. In addition, the brightness of t…

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…

Destination image refers to the mental schemes, beliefs and ideas of individuals about a place or destination. In the development of tourism, it is of utmost importance that the important products, the destinations, are made known and have a positive image in …

Görüntü bölütleme, görüntü işlemenin önemli aşamalarından biridir ve SRG (Seeded Region Growing – Tohumlu Bölge Genişletme) en bilinen bölge tabanlı bölütleme tekniklerindendir. Bu çalışmada tohum seçimlerinin, tohumlu alan genişletmedeki başarıya etkisi incel…

 In today's applications, a significant increase in the use of deep learning algorithms is noticeable. The convolution neural network (CNN) of deep learning has been used frequently recently, especially for the successful discrimination of people and vehicles …

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 …

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…

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 COVID-19 pandemic has necessitated the development of rapid, accurate, and automated diagnostic tools to assist healthcare professionals in patient screening and management. This comprehensive study presents a detailed comparative analysis of ten state-of-…

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…