Examining convolutional feature extraction using Maximum Entropy (ME) and Signal-to-Noise Ratio (SNR) for image classification
Version 2 2024-06-03, 02:58
Version 1 2024-04-17, 05:03
conference contribution
posted on 2024-06-03, 02:58 authored by N Gowdra, Roopak SinhaRoopak Sinha, S MacDonellExamining convolutional feature extraction using Maximum Entropy (ME) and Signal-to-Noise Ratio (SNR) for image classification
History
Volume
2020-OctoberPagination
471-476Location
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)Energy & FuelsEngineeringEngineering, Electrical & ElectronicEngineering, ManufacturingGRADIENTGreen & Sustainable Science & Technologyinformation propagationMaximum Entropy (ME)NETWORKSoverflowRoboticsScience & TechnologyScience & Technology - Other TopicsSignal-to-Noise (SNR)Technologyunderflow
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