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Automatic Latent Fingerprint Segmentation based on Orientation and Frequency Features

contributor authorRevathy, T.
contributor authorPramila, G.
contributor authorAdhiraja, A.
contributor authorAskerunisa, A.
date accessioned2020-03-12T21:37:12Z
date available2020-03-12T21:37:12Z
date issued2014
identifier other6950029.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1054763?show=full
formatgeneral
languageEnglish
publisherIEEE
titleAutomatic Latent Fingerprint Segmentation based on Orientation and Frequency Features
typeConference Paper
contenttypeMetadata Only
identifier padid8185447
subject keywordsgrid computing
subject keywordsn learning (artificial intelligence)
subject keywordsn pattern classification
subject keywordsn processor scheduling
subject keywordsn real-time systems
subject keywordsn application scheduling
subject keywordsn grid computing
subject keywordsn learning curve
subject keywordsn real system
subject keywordsn resource scheduling
subject keywordsn scheduling algorithm classification
subject keywordsn scheduling methodology
subject keywordsn scheduling system
subject keywordsn simulation based approach
subject keywordsn Grid computing
subject keywordsn Job shop scheduling
subject keywordsn Monitoring
subject keywordsn Scheduling algorithms
subject keywordsn Scheduling in Grid
subject keywordsn application schedu
identifier doi10.1109/ACCT.2014.32
journal titleommunications and Signal Processing (ICCSP), 2014 International Conference on
filesize1038472
citations0


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