Deep Learning for Consumer Devices and Services 3-Getting More From Your Datasets With Data Augmentation

Peter Corcoran

doi:10.1109/MCE.2019.2959062

Deep Learning for Consumer Devices and Services 3-Getting More From Your Datasets With Data Augmentation

Peter Corcoran

Electrical & Electronic Engineering

Research output: Contribution to a Journal (Peer & Non Peer) › Article › peer-review

Abstract

A key aspect to developing and successfully deploying neural network (NN)-based solutions is the availability of suitable datasets. In this article some of the challenges to acquire and annotate data are discussed in the context of new consumer devices. To increase the sample size of training data several approaches to augment a seed dataset are explained and discussed including a number of advanced, problem-specific techniques. A basic introduction to the concept of learned data augmentation is also provided.

Original language	English (Ireland)
Number of pages	5
Journal	IEEE Consumer Electronics Magazine
Volume	9
DOIs	https://doi.org/10.1109/MCE.2019.2959062
Publication status	Published - 1 May 2020

Authors (Note for portal: view the doc link for the full list of authors)

Authors
Corcoran, P;Costacke, C;Varkarakis, V;Lemley, J
Corcoran, P,Costacke, C,Varkarakis, V,Lemley, J

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10.1109/MCE.2019.2959062

Cite this

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Deep Learning for Consumer Devices and Services 3-Getting More From Your Datasets With Data Augmentation

Abstract

Authors (Note for portal: view the doc link for the full list of authors)

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Cite this