Making Convolutional Neural Networks Energy-Efficient: An Introduction

As convolutional neural networks (CNNs) have become mainstream for object recognition and image classification, the environmental impact caused by their high energy consumption (EC) is non negligible.This paper examines techniques that have the ability to reduce the EC of CNNs.It also highlights the inconsistency of metrics that are used for estimating or measuring EC, which reduces the comparability of these techniques.This review aims to shed light on the current situation and to provide a basis for future research in green machine learning.