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Found 4 papers, 2 papers with code
CEC-CNN: A Consecutive Expansion-Contraction Convolutional Network for Very Small Resolution Medical Image Classification
However, an inherent side-effect of this is that high-level features, produced at the deep end of the network, are always captured in low resolution feature maps.
Sparsely Activated Networks
We lastly present Sparsely Activated Networks (SANs) that consist of kernels with shared weights that, during encoding, are convolved with the input and then passed through a sparse activation function.
Signal2Image Modules in Deep Neural Networks for EEG Classification
Deep learning has revolutionized computer vision utilizing the increased availability of big data and the power of parallel computational units such as graphical processing units.
Deep Learning in Cardiology
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently.
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