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Found 2 papers, 1 papers with code
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets
Ultimately, we reveal that DSC-based architectures such as MobileNets implicitly rely on cross-kernel correlations, while our BSConv formulation is based on intra-kernel correlations and thus allows for a more efficient separation of regular convolutions.
Ranked #18 on
Fine-Grained Image Classification
on Stanford Dogs
Impatient DNNs - Deep Neural Networks with Dynamic Time Budgets
We propose Impatient Deep Neural Networks (DNNs) which deal with dynamic time budgets during application.
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