Performance of GAN-based augmentation for deep learning COVID-19 image classification
Oleksandr Fedoruk, K. Klimaszewski, Aleksander Ogonowski, Rafał Możdżonek
Abstract
The biggest challenge in the application of deep learning to the medical domain is the availability of training data. Data augmentation is a typical methodology used in machine learning when confronted with a limited data set. In a classical approach image transformations i.e. rotations, cropping and brightness changes are used.
Topics & Concepts
Deep learningComputer scienceArtificial intelligenceTraining setDomain (mathematical analysis)BrightnessImage (mathematics)Data setCoronavirus disease 2019 (COVID-19)Set (abstract data type)CroppingData modelingMachine learningContextual image classificationComputer visionMathematicsDatabaseAgricultureMathematical analysisProgramming languageInfectious disease (medical specialty)PhysicsOpticsEcologyDiseaseBiologyPathologyMedicineCOVID-19 diagnosis using AIAI in cancer detectionAnomaly Detection Techniques and Applications