Search Results for author: Miguel de Prado

Found 7 papers, 1 papers with code

Robustifying the Deployment of tinyML Models for Autonomous mini-vehicles

no code implementations1 Jul 2020 Miguel de Prado, Manuele Rusci, Romain Donze, Alessandro Capotondi, Serge Monnerat, Luca Benini and, Nuria Pazos

We leverage a family of compact and high-throughput tinyCNNs to control the mini-vehicle, which learn in the target environment by imitating a computer vision algorithm, i. e., the expert.

Autonomous Driving Autonomous Navigation +1

Automated Design Space Exploration for optimised Deployment of DNN on Arm Cortex-A CPUs

no code implementations9 Jun 2020 Miguel de Prado, Andrew Mundy, Rabia Saeed, Maurizio Denna, Nuria Pazos, Luca Benini

The framework relies on a Reinforcement Learning search that, combined with a deep learning inference framework, automatically explores the design space and learns an optimised solution that speeds up the performance and reduces the memory on embedded CPU platforms.

Learning to infer: RL-based search for DNN primitive selection on Heterogeneous Embedded Systems

no code implementations18 Nov 2018 Miguel de Prado, Nuria Pazos, Luca Benini

In this work, we present QS-DNN, a fully automatic search based on Reinforcement Learning which, combined with an inference engine optimizer, efficiently explores through the design space and empirically finds the optimal combinations of libraries and primitives to speed up the inference of CNNs on heterogeneous embedded devices.

QUENN: QUantization Engine for low-power Neural Networks

no code implementations14 Nov 2018 Miguel de Prado, Maurizio Denna, Luca Benini, Nuria Pazos

Deep Learning is moving to edge devices, ushering in a new age of distributed Artificial Intelligence (AI).

Clustering Quantization

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