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Kanser, insan ölümlerine sebep olan hastalıklar arasında ikinci sırada gelmektedir. Günümüzde insanların kansere yakalanma oranları giderek artmaktadır. Kanser; kötü beslenme, sigara ve alkol kullanımı, uzun süre güneş ışığına maruz kalma gibi birçok nedenle o…

With the help of ability to imitate the biological nervous system, Spiking Neural Networks (SNNs) architectures have become popular recently. In order to benefit at the maximum level from the low power consumption, event-based structure and parallelization fea…

Complexity in the behavior of asphalt binders are further escalated with geopolymer (fly ash and the alkali liquid) modification thus, making it difficult to predict the performance of the binder accurately. This study employs artificial neural network model…

Yapay sinir ağları makine öğrenmesi alanında birçok problemin çözümünde sıklıkla kullanılmaktaydı. Fakat “Yapay Zeka Kışı” olarak da adlandırılan dönemde ilk olarak donanımsal kısıtlamalar ve diğer problemler sebebiyle bu alandaki çalışmalar durma noktasına ge…

Handwritten Signature Recognition (HSR) is a vital task in document authentication and verification systems. This paper proposes a novel approach for offline HSR leveraging pre-trained Convolutional Neural Network (CNN) models. CNNs have demonstrated remarkabl…

The aim of this study is to forecast installed wind power which is a one of the renewable energy resources in Turkey for the year of 2017 based on artificial neural network method using the normalized last ten-year data. An artificial neural network has been c…

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…

In this study, the effect of using a mixture of butanol and diesel fuel in a small diesel engine on engine performance and exhaust emissions is modeled. A comparison has been made with artificial neural networks, which is an up-to-date method, and multiple l…

This paper describes a laboratory application for the forecasting the dielectric properties, using an artificial neural network embedded in a microprocessor. The dielectric permittivity and loss factor of the insulation material were determined as a function o…

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…

Skin cancer is the abnormal growth of skin cells and one of the most common cancers of all. There are several types of skin cancer. Melanoma, a form of skin cancer, has increased 237% in Turkey in the last 30 years. While the U.S. adds about one million new ca…

Network security is becoming more and more important as a result of the growing use of the internet and technological developments. Intrusion Detection Systems (IDS) are utilized to detect attacks, preferably by monitoring real-time events. Therefore, they hol…

Complex-valued artificial neural network (CVANN) has been developed to process data with complex numbers directly. In a CVANN the weights, threshold, inputs and outputs are all complex numbers. The convergence of the CVANN back propagation algorithm depending …

In this paper, signal recognition system is proposed for classification of soil types and buried object by using feature extraction and artificial neural networks. Using GprMax simulation program, 300 GPR A scan signals were obtained for different ground plane…

Traffic flow forecasting has an important place in designing a successful intelligent transportation system. The success of the forecasting is related to the accuracy and timely acquisition of the traffic flow data. The inadequacy in the number of data has led…

The increasing world population has increased the demand for food. Many threats such as agricultural land use, environmental impacts, global warming and drought risks necessitate industrialization of agricultural production and optimum utilization of existing …

 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 …

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…

In recent years there has been an increasing interest in the study of various mathematical problems with variable exponent Lebesgue spaces. There are also a lot of published papers in these spaces. Spaces of weakly differentiable functions, so called Sobolev s…

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 …