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Efficient COVID-19 Segmentation from CT Slices Exploiting Semantic Segmentation with Integrated Attention Mechanism
(Sprınger, 2021)
Coronavirus (COVID-19) is a pandemic, which caused suddenly unexplained pneumonia cases and caused a devastating effect on global public health. Computerized tomography (CT) is one of the most effective tools for COVID-19 ...
Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models
(Sprınger, 2019)
Introduction Cardiotocography (CTG) consists of two biophysical signals that are fetal heart rate (FHR) and uterine contraction (UC). In this research area, the computerized systems are usually utilized to provide more ...
DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images
(Churchıll Lıvıngstone, 2020)
Recent studies have shown that convolutional neural networks (CNNs) can be more accurate, efficient and even deeper on their training if they include direct connections from the layers close to the input to those close to ...
Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation
(Churchıll Lıvıngstone, 2020)
Liver and hepatic tumor segmentation remains a challenging problem in Computer Tomography (CT) images analysis due to its shape variation and vague boundary. The general hypothesis says that deep learning methods produce ...
Efficient approach for digitization of the cardiotocography signals
(Elsevıer, 2020)
Cardiotocography (CTG) is generally provided on printed traces, and digitization of CTG signal is important for forthcoming assessments. In this paper, a new algorithm relies on the box-counting method is offered for the ...
Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images
(Elsevıer, 2019)
Breast cancer (BC) is one of the most frequent types of cancer that adult females suffer from worldwide. Many BC patients face irreversible conditions and even death due to late diagnosis and treatment. Therefore, early ...
Transfer learning based histopathologic image classification for breast cancer detection
(Sprınger, 2018)
Breast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment. Thus, in recent years, early breast cancer detection systems ...
An Effective Hybrid Model for EEG-Based Drowsiness Detection
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2019)
Early detection of driver drowsiness and the development of a functioning driver alertness system may support the prevention of numerous vehicular accidents worldwide. Wearable sensors and camera-based systems are generally ...
Automatic Airport Detection with Line Segment Detector and Histogram of Oriented Gradients from Satellite Images
(Ieee, 2018)
Airports are extremely critical targets in both economic and military areas. The earlier detection of these regions provides a very important intelligence information for making that regions unusable against a possible ...
Efficient deep features selections and classification for flower species recognition
(Elsevıer Scı Ltd, 2019)
Image-based automatic flower species classification is an important problem for the biologists who construct digital flower catalogs. A dozen of work about flower species recognition has been proposed so far based on ...
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