activity
20172022
most citedNEURAghe: Exploiting CPU-FPGA Synergies for Efficient and Flexible CNN Inference Acceleration on Zynq SoCs

67 citations · 68 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022

An adaptable cognitive microcontroller node for fitness activity recognition

Matteo Antonio Scrugli, Bojan Blažica, Paolo Meloni

The new generation of wireless technologies, fitness trackers, and devices with embedded sensors can have a big impact on healthcare systems and quality of life. Among the most cru…

cs.LG2021

An adaptive cognitive sensor node for ECG monitoring in the Internet of Medical Things

Matteo Antonio Scrugli, Daniela Loi, Luigi Raffo +1

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials and healthcare procedures. Cardiovascular diseases monitoring, usually involving e…

cs.AR2021

Proceedings of the DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021)

Frank Hannig, Paolo Meloni, Matteo Spallanzani +1

This volume contains the papers accepted at the first DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021), held virtua…

eess.SP2020★ 1 cited

Optimizing Temporal Convolutional Network inference on FPGA-based accelerators

Marco Carreras, Gianfranco Deriu, Luigi Raffo +2

Convolutional Neural Networks are extensively used in a wide range of applications, commonly including computer vision tasks like image and video classification, recognition, and s…

cs.NE2017★ 67 cited

NEURAghe: Exploiting CPU-FPGA Synergies for Efficient and Flexible CNN Inference Acceleration on Zynq SoCs

Paolo Meloni, Alessandro Capotondi, Gianfranco Deriu +5

Deep convolutional neural networks (CNNs) obtain outstanding results in tasks that require human-level understanding of data, like image or speech recognition. However, their compu…