Results 131 to 140 of about 79,494 (188)

Generating interaction gestures in dyadic conversations using a diffusion model. [PDF]

PLoS One
Okadome Y, Alkatshah Y, Nakamura Y.
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A pediatric case of diphthamide biosynthesis 1 gene defect presenting with developmental delay, short stature, dysmorphic features, and sparse hair (Loucks-Innes syndrome): a case report. [PDF]

J Med Case Rep
Al-Ajlouni YA, Lihaz M, Islam M.
europepmc   +1 more source

PH-SHOWOA: Parallel hybrid SHO-WOA for VRPSPDTW. [PDF]

PLoS One
Nguyen T, Vaclav S, Vo B, Nguyen VD.
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Editing and synthetic engineering of chloroplast genomes. [PDF]

Plant Commun
Fu J, Zhang J.
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The association between specific cognitive domains function and gait performance or postural control in post-stroke participants: a cross-sectional study. [PDF]

Front Neurol
Wang Y, Wang L, Zhou J, Deng M, Qiao Y, Rong J.   +5 more
europepmc   +1 more source

The plasmid-host fitness landscape: a new paradigm for predicting the fate of mobile resistance. [PDF]

Appl Environ Microbiol
Abdulqadir HN.
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HiFi sequencing accurately identifies clinically relevant variants in paralogous genes

van der Sanden B, Betz C, Herzog K, Schamschula E, Wimmer K, Vater I, Balachandran S, Chen X, Corominas Galbany J, Timmermans R, Derks R, HiFi Solves EMEA Consortium, Spielmann M, Eberle MA, Gilissen C, Vissers LE, Zschocke J, Bolz HJ, Hoischen A.   +18 more
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Adaptive matching for copy-move Forgery detection

2014 IEEE International Workshop on Information Forensics and Security (WIFS), 2014
The objective of copy-move forgery detection methods are to find copied regions within the same image. There are two main approaches to detect copy-move forgery: keypoint-based and block-based methods. Although the former is superior in terms of computational complexity, these methods neglect the smooth regions since they confine their search to ...
Zandi, Mohsen, Mahmoudi-Aznaveh, Ahmad, Azadeh Mansouri   +2 more
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Copy-Move Forgery Detection Using DyWT

International Journal of Multimedia Data Engineering and Management, 2017
In this paper, we proposed a passive method for copy-move region duplication detection using dyadic wavelet transform (DyWT). DyWT is better than discrete wavelet transform (DWT) for data analysis as it is shift invariant. Initially we decompose the input image into approximation (LL1) and detail (HH1) sub-bands.
Choudhary Shyam Prakash, Sushila Maheshkar   +1 more
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