Search Results for author: Marco Piastra

Found 5 papers, 1 papers with code

Conditional Deep Convolutional Neural Networks for Improving the Automated Screening of Histopathological Images

no code implementations29 May 2021 Gianluca Gerard, Marco Piastra

We adapted to our task a co-FCN originally applied to organs segmentation in volumetric medical images and we trained it on the Whole Slide Images (WSIs) from three out of five medical centers present in the CAMELYON17 dataset.

Semantic Segmentation whole slide images

Pre-trainable Reservoir Computing with Recursive Neural Gas

no code implementations25 Jul 2018 Luca Carcano, Emanuele Plebani, Danilo Pietro Pau, Marco Piastra

Echo State Networks (ESN) are a class of Recurrent Neural Networks (RNN) that has gained substantial popularity due to their effectiveness, ease of use and potential for compact hardware implementation.

Online Fall Detection using Recurrent Neural Networks

1 code implementation13 Apr 2018 Mirto Musci, Daniele De Martini, Nicola Blago, Tullio Facchinetti, Marco Piastra

This information can be used to trigger the necessary assistance in case of injury.

Some Further Evidence about Magnification and Shape in Neural Gas

no code implementations28 Mar 2015 Giacomo Parigi, Andrea Pedrini, Marco Piastra

Neural gas (NG) is a robust vector quantization algorithm with a well-known mathematical model.


A Multi-signal Variant for the GPU-based Parallelization of Growing Self-Organizing Networks

no code implementations28 Mar 2015 Giacomo Parigi, Angelo Stramieri, Danilo Pau, Marco Piastra

Among the many possible approaches for the parallelization of self-organizing networks, and in particular of growing self-organizing networks, perhaps the most common one is producing an optimized, parallel implementation of the standard sequential algorithms reported in the literature.

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