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Combined SIFT and bi-coherence features to detect image forgery

contributor authorJu Zhang
contributor authorQiuqi Ruan
contributor authorYi Jin
date accessioned2020-03-12T22:34:44Z
date available2020-03-12T22:34:44Z
date issued2014
identifier other7015314.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1087657?show=full
formatgeneral
languageEnglish
publisherIEEE
titleCombined SIFT and bi-coherence features to detect image forgery
typeConference Paper
contenttypeMetadata Only
identifier padid8225531
subject keywordscompressed sensing
subject keywordsn learning (artificial intelligence)
subject keywordsn object tracking
subject keywordsn statistical analysis
subject keywordsn benchmark videos
subject keywordsn best object location
subject keywordsn drifting
subject keywordsn generative methods
subject keywordsn improved compressive tracking algorithm
subject keywordsn local context information
subject keywordsn local context learning
subject keywordsn low-level features
subject keywordsn object location likelihood function
subject keywordsn occlusion
subject keywordsn statistical correlation
subject keywordsn Computed tomography
subject keywordsn Context
subject keywordsn Context modeling
subject keywordsn Feature extraction
subject keywordsn Target
identifier doi10.1109/ChiCC.2014.6895730
journal titleignal Processing (ICSP), 2014 12th International Conference on
filesize788382
citations2


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