217 citations · 409 across the 17 of their papers we have counts for
5 papers · 1 filter
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio +3
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to au…
NASCaps: A Framework for Neural Architecture Search to Optimize the Accuracy and Hardware Efficiency of Convolutional Capsule Networks
Alberto Marchisio, Andrea Massa, Vojtech Mrazek +3
Deep Neural Networks (DNNs) have made significant improvements to reach the desired accuracy to be employed in a wide variety of Machine Learning (ML) applications. Recently the Go…
An Efficient Spiking Neural Network for Recognizing Gestures with a DVS Camera on the Loihi Neuromorphic Processor
Riccardo Massa, Alberto Marchisio, Maurizio Martina +1
Spiking Neural Networks (SNNs), the third generation NNs, have come under the spotlight for machine learning based applications due to their biological plausibility and reduced com…
NeuroAttack: Undermining Spiking Neural Networks Security through Externally Triggered Bit-Flips
Valerio Venceslai, Alberto Marchisio, Ihsen Alouani +2
Due to their proven efficiency, machine-learning systems are deployed in a wide range of complex real-life problems. More specifically, Spiking Neural Networks (SNNs) emerged as a…
Q-CapsNets: A Specialized Framework for Quantizing Capsule Networks
Alberto Marchisio, Beatrice Bussolino, Alessio Colucci +3
Capsule Networks (CapsNets), recently proposed by the Google Brain team, have superior learning capabilities in machine learning tasks, like image classification, compared to the t…