• Relational Turkish Text Classification Using Distant Supervised Entities and Relations 

  Okur, Halil İbrahim; Tohma, Kadir; Sertbaş, Ahmet (Tech Science Press, 2024)

  Text classification, by automatically categorizing texts, is one of the foundational elements of natural language processing applications. This study investigates how text classification performance can be improved through ...

• Trainable Self-Guided Filter for Multi-Focus Image Fusion 

  Karacan, Levent (Institute of Electrical and Electronics Engineers Inc., 2023)

  Cameras are limited in their ability to capture all-in-focus images due to their limited depth of field. This results in blurriness for objects too far in front of or behind the focused point. To overcome this limitation, ...

• Gish: a novel activation function for image classification 

  Kaytan, Mustafa; Aydilek, İbrahim Berkan; Yeroğlu, Celaleddin (Springer, 2023)

  In Convolutional Neural Networks (CNNs), the selection and use of appropriate activation functions is of critical importance. It has been seen that the Rectified Linear Unit (ReLU) is widely used in many CNN models. Looking ...

• Parameter Selection in Elliptical Fourier Series for Leaf Classification 

  Atasoy, Hüseyin; Kutlu, Yakup (Dokuz Eylül Üniversitesi, 2022)

  Elliptical Fourier series method is a relatively old but powerful method in contour analysis. We have previously implemented this method as a module for a computer program called “BioMorph”. There are two significant ...

• CLAHE based Enhancement to Transfer Learning in COVID-19 Detection 

  Altan, Gökhan; Narlı, Süleyman Serhan (Gazi Akademi Yayıncılık, 2022)

  Early diagnosis of COVID-19 disease becomes possible with the enhancements on feature learning and advanced pre-processing stages for classification of chest X-ray images using deep learning. Besides, high-performance ...

• Performance Analysis of CNN Channel Attention Modules for Image Classification Task 

  Sarıgül, Mehmet (Çukurova Üniversitesi, 2023)

  ncreasing the representation power of convolutional neural networks, a popular deep learning model, is one of the hot study topics recently. Channel attention is a common strategy followed in this regard. In this strategy, ...

• Fibonacci Collocation Method for Solving a Class of Nonlinear Di erential Equations 

  Çakmak, Musa; Alkan, Sertan (Mathematicians AssociationMatematikçiler Derneği, 2023)

  In this study, a collocation method based on Fibonacci polynomials is used for approximately solving a class of nonlinear differential equations with initial conditions. The problem is firstly reduced into a nonlinear ...

• Region contrastive camera localization 

  Sarıgül, Mehmet; Karacan, Levent (Elsevier, 2023)

  Visual camera localization is a well-studied computer vision problem and has many applications. Recently, deep convolutional neural networks have begun to be utilized to solve six-degree-of-freedom (6-DoF) camera pose ...

• Adaptive second order sliding mode guidance law for missile-target interception with fuzzy logic system 

  Gürsoy-Demir, Handan; Efe, Mehmet Önder (SAGE Publications, 2023)

  This paper presents the design of a 3D missile guidance law based on a second order sliding mode control technique employing an adaptive tuning law and a fuzzy gain scheduling. At the outset, the super-twisting sliding ...

• A survey on digital video stabilization 

  Sarıgül, Mehmet (Springer, 2023)

  Shakes and jitters are an eventual result of involuntary camera movements during video recording. Digital video stabilization is the elimination of these errors with smart algorithms. This process is usually performed in ...

• Sentiment Analysis in Turkish Question Answering Systems: An Application of Human-Robot Interaction 

  Tohma, Kadir; Okur, Halil İbrahim; Kutlu, Yakup; Sertbaş, Ahmet (Institute of Electrical and Electronics Engineers Inc., 2023)

  The use of the sentiment analysis technique, which aims to extract emotions and thoughts from texts, has become a remarkable research topic today, where the importance of human-robot interaction is gradually increasing. ...

• Modelling Routing Attacks on Collection Tree Protocol and Designing an Intrusion Detection System on Real-Time Wireless Sensor Networks 

  Oflazoğlu, Çağlar; Turgut, İpek Abasıkeleş (Academic Platform Journal of Engineering and Science, 2020)

  Kablosuz Algılayıcı Ağlar (KAA), günümüzde IoT sistemlerin kullanımlarının artması ile birlikte önem kazanan konulardan birisi haline gelmiştir. KAA’yı oluşturan düğümlerin sınırlı kaynaklara sahip olması ile birlikte ...

• Yaprak Sınıflandırmak için Yeni Bir Evrişimli Sinir Ağı Modeli Geliştirilmesi 

  Camgözlü, Yunus; Kutlu, Yakup (Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi, 2021)

  Doğanın bir parçası olan bitkiler çevremize güzellik katmanın yanı sıra alternatif tıp gibi farklı sebep için de kullanılmaktadır. Bu gibi uzmanlık gerektiren durumlarda halk arasında yayılan yanlış bilgilerle zehirli ...

• Bul-Tak Oyuncağı Şekillerinin Klasik Görüntü İşleme ve Derin Öğrenme Yöntemleri ile Tespiti 

  Dersuneli, Mehmet; Gündüz, Taner; Kutlu, Yakup (Bitlis Eren Üniversitesi, 2021)

  Bilgisayar görme algoritmaları, teknolojinin ilerlemesiyle daha kullanılır hale gelmektedir. Klasik yöntemler olan görüntü işleme ve makine öğrenmesi algoritmaları ile yapılan bilgisayarlı görü uygulamaları halen kullanılsa ...

• MSDeveloper: A Variability-Guided Methodology for Microservice-Based Development 

  Dolu, Betül Kuruoğlu; Çetinkaya, Anıl; Kaya, M. Çağrı; Nazlıoğlu, Selma; Doǧru, Ali Hikmet (MDPI, 2022)

  This article presents a microservice-based development approach, MSDeveloper (Microservices Developer), employing variability management for product configuration through a low-code development environment. The purpose of ...

• A numerical method for solving a class of systems of nonlinear Pantograph differential equations 

  Çakmak, Musa; Alkan, Sertan (Elsevier, 2022)

  In this paper, Fibonacci collocation method is firstly used for approximately solving a class of systems of nonlinear Pantograph differential equations with initial conditions. The problem is firstly reduced into a nonlinear ...

• A novel fractional operator application for neural networks using proportional Caputo derivative 

  Altan, Gökhan; Alkan, Sertan; Baleanu, Dumitru (Springer, 2022)

  In machine learning models, one of the most popular models is artificial neural networks. The activation function is one of the important parameters of neural networks. In this paper, the sigmoid function is used as an ...

• DeepOCT: An explainable deep learning architecture to analyze macular edema on OCT images 

  Altan, Gökhan (Elsevier, 2022)

  Macular edema (ME) is one of the most common retinal diseases that occur as a result of the detachment of the retinal layers on the macula. This study provides computer-aided identification of ME for even small pathologies ...

• Prediction of Li-Ion Battery Discharge Patterns in IoT Devices Under Random Use Via Machine Learning Algorithms 

  Gökçen, Ahmet; Gökçen, Alkım; Şahin, Savaş (Oxford University Press, 2022)

  This study presents foreseeing of the Lithium-ion battery discharge models for the Internet of Things (IoT) devices under randomized use patterns. IoT systems run in harmony with the human-machine interface, communication ...

• A nonlinear disturbance observer-based adaptive integral sliding mode control for missile guidance system 

  Gürsoy-Demir, Handan; Önder Efe, Mehmet (Taylor and Francis Ltd., 2022)

  A novel composite three-dimensional (3D) guidance law based on an adaptive integral sliding mode (AISM) control utilizing a nonlinear disturbance observer (NDOB) technique is proposed for missiles. First, an integral sliding ...

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