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Deep neural network model with Bayesian optimization for tuberculosis detection from X-Ray images
(Springer, 2023)Tuberculosis is a chronic lung disease caused by bacterial infection, and more than 10 million people get this disease every year, especially in developing countries. Early diagnosis of tuberculosis is important for effective ... -
A Stacking Ensemble Learning Approach for Intrusion Detection System
(Düzce Üniversitesi, 2021)Intrusion detection systems (IDSs) have received great interest in computer science, along with increased network productivity and security threats. The purpose of this study is to determine whether the incoming network ... -
Akciğer Histopatoloji Görüntülerinden Çıkarılan Derin Özellikleri Kullanan Makine Öğrenmesi Sınıflandırıcıları ile Akciğer Kanseri Tespiti
(Bitlis Eren Üniversitesi, 2021)Kanser dünyada ve ülkemizde gözlenme sıklığı giderek artan sağlık sorunlarının başında gelmekte ve her yıl milyonlarca insan kanser nedeniyle hayatını kaybetmektedir. Histopatolojik tanı, kanser türünün teşhisinde ve tedavi ... -
Using Machine Learning Algorithms for Jumping Distance Prediction of Male Long Jumpers
(Journal of Intelligent Systems: Theory and Applications, 2022)The long jump is defined as an athletic event, and it has also been a standard event in modern Olympic Games. The purpose of the athletes is to make the distance as far as possible from a jumping point. The main purpose ... -
Prediction of sports attendance: A comparative analysis
(SAGE Publications, 2022)In this study, a comparative analysis for predicting sports attendance demand is presented based on econometric, artificial intelligence, and machine learning methodologies. Data from more than 20,000 games from three major ... -
Classification of myositis from muscle ultrasound images using deep learning
(Elsevier, 2022)Inflammatory myopathies, are rare muscle diseases. As a result of the body's own immune system attacking by targeting the muscle cells, muscle weakness develops due to inflammation in the muscles. Early and definitive ... -
Phishing Detection System Using Extreme Learning Machines with Different Activation Function based on Majority Voting
(Gazi Üniversitesi, 2022)Phishing is a type of software-based cyber-attack carried out to steal private information such as login credentials, user passwords, and credit card information. When the security reports published in recent years are ... -
Automatic segmentation of COVID-19 from computed tomography images using modified U-Net model-based majority voting approach
(Springer, 2022)The coronavirus disease (COVID-19) is an important public health problem that has spread rapidly around the world and has caused the death of millions of people. Therefore, studies to determine the factors affecting the ... -
Classification of Different Tympanic Membrane Conditions Using Fused Deep Hypercolumn Features and Bidirectional LSTM
(Elsevier, 2022)Objectives: Middle ear inflammatory diseases are global health problem that can have serious consequences such as hearing loss and speech disorders. The high cost of medical devices such as otoendoscope and oto-microscope ... -
A novel image Denoising approach using super resolution densely connected convolutional networks
(Springer, 2022)Image distortion effects, called noise, may occur due to various reasons such as image acquisition, transfer, and duplication. Image denoising is a preliminary step for many studies in the field of image processing. The ... -
Glokom Hastalığının Evrişimli Sinir Ağı Mimarileri ile Tespiti
(Dokuz Eylül Üniversitesi Mühendislik Fakültesi, 2021)Glokom, genellikle göz içi basıncının yükselmesi nedeniyle optik sinire zarar veren bir hastalıktır ve dünya genelinde geri döndürülemez körlüğün yaygın bir sebebidir. Ancak hastalık erken dönemde tespit edilebilirse ... -
Classification of Different Tympanic Membrane Conditions Using Fused Deep Hypercolumn Features and Bidirectional LSTM
(Elsevier, 2021)Objectives: Middle ear inflammatory diseases are global health problem that can have serious consequences such as hearing loss and speech disorders. The high cost of medical devices such as oto-endoscope and oto-microscope ... -
Automated detection of Covid-19 disease using deep fused features from chest radiography images
(Elsevier, 2021)The health systems of many countries are desperate in the face of Covid-19, which has become a pandemic worldwide and caused the death of hundreds of thousands of people. In order to keep Covid-19, which has a very high ... -
Plant leaf disease classification using EfficientNet deep learning model
(Elsevier, 2021)Most plant diseases show visible symptoms, and the technique which is accepted today is that an experienced plant pathologist diagnoses the disease through optical observation of infected plant leaves. The fact that the ... -
Carbon footprint forecasting using time series data mining methods: the case of Turkey
(Springer, 2021)In the globalizing world, many factors such as rapidly increasing population, production and consumption habits, and economic growth cause climate changes. The carbon footprint is a measure of CO2 emissions released into ... -
Computer-Aided Detection of Lung Nodules in Chest X-Rays using Deep Convolutional Neural Networks
(Sakarya Üniversitesi Bilgisayar ve Bilişim Bilimleri Dergisi (Online), 2019)Chest X-Rays are most accessible medical imaging technique for diagnosing abnormalities in the heart and lung area. Automatically detecting these abnormalities with high accuracy could greatly enhance real world diagnosis ...
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