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WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network
(Pergamon-Elsevıer Scıence Ltd, 2021)
This paper introduces a novel deep neural network (WSFNet) to efficiently forecast multi-step ahead wind speed. WSFNet forms the basis of the stacked convolutional neural network (CNN) with dense connections of different ...
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 ...
An improved residual-based convolutional neural network for very short-term wind power forecasting
(Pergamon-Elsevıer Scıence Ltd, 2021)
An accurate forecast of wind power is very important in terms of economic dispatch and the operation of power systems. However, effectively mitigating the risks arising from wind power in power system operations greatly ...
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 ...