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Detection and prioritization of COVID-19 infected patients from CXR images: Analysis of AI-assisted diagnosis in clinical settings
In this paper, we present the significant results from the Covid Radiographic imaging System based on AI (Co.R.S.A.) project, which …
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Loss-based sensitivity regularization: towards deep sparse neural networks
LOBSTER (LOss-Based SensiTivity rEgulaRization) is a method for training neural networks having a sparse topology. Let the sensitivity …
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Simplify: A python library for optimizing pruned neural networks
Neural network pruning allows for impressive theoretical reduction of models sizes and complexity. However it usually offers little …
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Serene: Sensitivity-based regularization of neurons for structured sparsity in neural networks
Deep neural networks include millions of learnable parameters, making their deployment over resource-constrained devices problematic. …
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Unveiling covid-19 from chest x-ray with deep learning: a hurdles race with small data
The possibility to use widespread and simple chest X-ray (CXR) imaging for early screening of COVID-19 patients is attracting much …
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