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Atrial Fibrillation Detection Using Deep Features and Convolutional Networks
The first approach used a pretrained DenseNet model to extract features that were then classified using Support Vector Machines, and the second approach used the spectrograms as direct input into a convolutional network.
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Atrial Fibrillation Detection
on MIT-BIH AF
The Effects of Image Pre- and Post-Processing, Wavelet Decomposition, and Local Binary Patterns on U-Nets for Skin Lesion Segmentation
Skin cancer is a widespread, global, and potentially deadly disease, which over the last three decades has afflicted more lives in the USA than all other forms of cancer combined.
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