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Francesco Barchi, Emanuele Parisi, Andrea Bartolini and Andrea Acquaviva
To cope with the increasing complexity of digital systems programming, deep learning techniques have recently been proposed to enhance software deployment by analysing source code for different purposes, ranging from performance and energy improvement to...
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De-Cheng Feng, Cheng-Zhuo Xiong, Emanuele Brunesi, Fulvio Parisi and Gang Wu
Precast concrete (PC) plays an important role in the industrialization processes of buildings, so it is critical to study the seismic performance of such structures. Several experimental and numerical studies have been conducted to investigate the behavi...
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Francesco Barchi, Luca Zanatta, Emanuele Parisi, Alessio Burrello, Davide Brunelli, Andrea Bartolini and Andrea Acquaviva
In this work, we present an innovative approach for damage detection of infrastructures on-edge devices, exploiting a brain-inspired algorithm. The proposed solution exploits recurrent spiking neural networks (LSNNs), which are emerging for their theoret...
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