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Deep Learning with ConvNet Predicts Imagery Tasks Through EEG
(Springer, 2021)
Deep learning with convolutional neural networks (ConvNets) has dramatically improved the learning capabilities of computer vision applications just through considering raw data without any prior feature extraction. Nowadays, ...
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 ...
Chronic obstructive pulmonary disease severity analysis using deep learning on multi-channel lung sounds
(Türkiye Klinikleri, 2020)
Chronic obstructive pulmonary disease (COPD) is one of the deadliest diseases which cannot be treated but can be kept under control in certain stages. COPD has five severities, including at-risk, mild, moderate, severe, ...