deep-learning

Design Environment of Quantization-Aware Edge AI Hardware for Few-Shot Learning

This study aims to ensure consistency in accuracy throughout the entire design flow in the implementation of edge AI hardware for few-shot learning, by implementing fixed-point data processing in the pre-training and evaluation phases. Specifically, …

Pipelined Architecture for a Semantic Segmentation Neural Network on FPGA

Many machine vision tasks like urban sceneunderstanding rely on machine learning, and more specifically deep neural networks to provide accurate enough results to make technology like autonomous vehicles possible. FPGAs have proven to be an excellent …

Pipelined Architecture for a Semantic Segmentation Neural Network on FPGA

Many machine vision tasks like urban sceneunderstanding rely on machine learning, and more specifically deep neural networks to provide accurate enough results to make technology like autonomous vehicles possible. FPGAs have proven to be an excellent …

PEFSL

PEFSL is a modular pipeline for the training, compilation, hardware synthesis and deployment of a few-shot learning application on an FPGA SoC.