Examining and Mitigating Kernel Saturation in Convolutional Neural Networks using Negative Images
Version 2 2024-06-03, 02:58
Version 1 2024-04-12, 06:55
conference contribution
posted on 2024-06-03, 02:58 authored by N Gowdra, Roopak SinhaRoopak Sinha, S MacDonellExamining and Mitigating Kernel Saturation in Convolutional Neural Networks using Negative Images
History
Volume
2020-OctoberPagination
465-470Location
SingaporePublisher DOI
Start date
2020-10-19End date
2020-10-21ISSN
1553-572XISBN-13
9781728154145Language
engPublication classification
E1.1 Full written paper - refereedTitle of proceedings
IECON 2020 : Proceedings of the 46th Annual Conference of the IEEE Industrial Electronics SocietyEvent
Industrial Electronics Society. Conference (2020 : 46th : Singapore)Publisher
IEEEPlace of publication
Piscataway, N.J.Series
IEEE Industrial Electronics SocietyPublication URL
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Keywords
Automation & Control SystemsComputer ScienceComputer Science, Information SystemsComputer Science, Theory & Methodsconvolutional neural network (CNN)data augmentationEnergy & FuelsEngineeringEngineering, Electrical & ElectronicEngineering, ManufacturingentropyGreen & Sustainable Science & TechnologyKernel Saturationnegative imagesRoboticsScience & TechnologyScience & Technology - Other TopicsTechnology
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