Classification of Hyperspectral Image using Convolutional Neural Network to Detect Coastal Water Features

DC Field Value Language
dc.contributor.author 김태호 -
dc.contributor.author 양찬수 -
dc.date.accessioned 2020-07-15T09:53:39Z -
dc.date.available 2020-07-15T09:53:39Z -
dc.date.created 2020-02-11 -
dc.date.issued 2018-11-08 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/22885 -
dc.description.abstract In this study, classification method of hyperspectral images using convolutional neural network (CNN) is introduced. In general, two-dimensional image data are used as the inputs of CNN classification model. Therefore, 2-D input data for each of the image pixels under specific area were prepared by using the reflectance values in all spectral bands. Thus, two-dimensional grey scale image of 1296 pixels was generated for each pixel under the region of interest (ROI) area obtained from PIKA-II hyperspectral camera. A CNN network was constructed to distinguish human, sea, sand, ship and rock in the image. The CNN model training based classification for each target was performed which resulted in highest classification accuracy for the sand (86.4%).ch of the image pixels under specific area were prepared by using the reflectance values in all spectral bands. Thus, two-dimensional grey scale image of 1296 pixels was generated for each pixel under the region of interest (ROI) area obtained from PIKA-II hyperspectral camera. A CNN network was constructed to distinguish human, sea, sand, ship and rock in the image. The CNN model training based classification for each target was performed which resulted in highest classification accuracy for the sand (86.4%). -
dc.description.uri 1 -
dc.language English -
dc.publisher THE INSTITUTE OF ELECTRONICS, INFORMATION AND COMMUNICATION ENGINEERS -
dc.relation.isPartOf International Conference on Space, Aeronautical and Navigational Electronics 2014 -
dc.title Classification of Hyperspectral Image using Convolutional Neural Network to Detect Coastal Water Features -
dc.type Conference -
dc.citation.conferencePlace JA -
dc.citation.endPage 156 -
dc.citation.startPage 153 -
dc.citation.title International Conference on Space, Aeronautical and Navigational Electronics 2014 -
dc.contributor.alternativeName 김태호 -
dc.contributor.alternativeName 양찬수 -
dc.identifier.bibliographicCitation International Conference on Space, Aeronautical and Navigational Electronics 2014, pp.153 - 156 -
dc.description.journalClass 1 -
Appears in Collections:
Marine Domain Management Research Division > Marine Security and Safety Research Center > 2. Conference Papers
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