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cs.CV2024
Squeeze-and-Remember Block
Rinor Cakaj, Jens Mehnert, Bin Yang
Convolutional Neural Networks (CNNs) are important for many machine learning tasks. They are built with different types of layers: convolutional layers that detect features, dropou…
cs.CV2024
Spectral Wavelet Dropout: Regularization in the Wavelet Domain
Rinor Cakaj, Jens Mehnert, Bin Yang
Regularization techniques help prevent overfitting and therefore improve the ability of convolutional neural networks (CNNs) to generalize. One reason for overfitting is the comple…
cs.CV2024
CNN Mixture-of-Depths
Rinor Cakaj, Jens Mehnert, Bin Yang
We introduce Mixture-of-Depths (MoD) for Convolutional Neural Networks (CNNs), a novel approach that enhances the computational efficiency of CNNs by selectively processing channel…