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Oscar Ferraz

2 accepted papers

2023

Benchmarking Convolutional Neural Network Inference on Low-Power Edge Devices

ICASSP 2023accepted

The massive adoption of IoT devices, the recent developments in the efficiency of AI systems, and the increase of edge computational power, accelerated the deployment of edge AI systems. The implementation of these systems through the use of low-power embedded devices scattered across the edges of a…

Cited by 0SourceScholar
2020

1.5GBIT/S 4.9W Hyperspectral Image Encoders on a Low-Power Parallel Heterogeneous Processing Platform

ICASSP 2020accepted

This work explores the utilization of low-power heterogeneous devices for parallelizing the compute-intensive hyper-spectral and multispectral image compression CCSDS-123 entropy encoders. Multithread processing allows for the near-optimal system's bandwidth to be exploited increasing the system ove…

Cited by 0SourceScholar