FRT

(redirected from Face Recognition Techniques)
Category filter:
AcronymDefinition
FRTFreight
FRTFremont (Amtrak bus station code; Fremont, CA)
FRTFort
FRTFries Research & Technology GmbH (Germany)
FRTFederal Realty Investment Trust
FRTFacial Recognition Test (neurology)
FRTFace Recognition Techniques
FRTFondation René Touraine (Frrench dermatology foundation)
FRTFirst Registration Tax (Hong Kong)
FRTFacility Response Team (US Navy)
FRTFast Response Time
FRTFrequency Response Test
FRTFord Racing Technology
FRTFacial Recognition Technology
FRTFox Pro Report
FRTFire Retardant Treated (wood construction)
FRTFor Real Tho
FRTFaculty Release Time (various schools)
FRTFlight Readiness Test (US NASA)
FRTForest Resource Trust (Oregon)
FRTFault Ride-Through (wind turbine energy)
FRTFemale Reproductive Tract
FRTFixed Radius Transition (aviation)
FRTFluides Réactifs et Turbulence (French: Reagents and Fluid Turbulence)
FRTFast Repetitive Tick (biology)
FRTFonds de la Recherche Technologique (French: technological research funds)
FRTFirst Response Team
FRTFloating Raft Technology (hydroponics)
FRTFirearms Reference Table
FRTFreightage
FRTFloating Roof Tank (oil storage)
FRTFrance Réseaux Télécommunications (French: French Telecommunications Networks)
FRTForward Repair Team
FRTFamily Reunion Travel
FRTFly River Turtle (turtle species)
FRTFlame Retardant Treated (wood processing)
FRTFast Response Team
FRTFix Response Time (TL 9000)
FRTFreight Tons (shipping)
FRTFloating Rototiller
FRTFederally Related Transaction (real estate appraisals)
FRTFungal Research Trust (UK)
FRTFast Rule Theorem
FRTFree Return Trajectory
FRTFlow Recording Transmitter
FRTFlippase Recognition Target
FRTFinland Racing Team (auto racing)
FRTFixed Radio Transmitter
FRTFraction of Residential Power Supplied by Traditional Sources (Carolina Environmental Program)
FRTFull Routing Table
Copyright 1988-2018 AcronymFinder.com, All rights reserved.
References in periodicals archive ?
Meanwhile, the face recognition technique enhances the functionality and security of the wireless network [9].
Most of the existing face recognition techniques used in controlled systems deteriorate in their performance when used in uncontrolled environments.
Today several different face recognition techniques are present each with a different approach; still there are challenges which need to be addressed.
Azeem, "A survey: linear and nonlinear PCA based face recognition techniques," International Arab Journal of Information Technology, vol.
Murtaza, "A survey: face recognition techniques under partial occlusion," IAJIT Issues, vol.
The accuracy results for the proposed AAPSO-SVM and the existing PSOSVM face recognition techniques, applied to the YALE and CASIA databases, with the different conditions, are shown in Table 2 and Figure 8.
We measured the t-test values for the accuracy between AAPSO-SVM and PSO-SVM face recognition techniques. There was not much variation in the t-test results; however, the t-test result shows that the proposed AAPSO-SVM is statistically significant and that it outperforms the PSO-SVM with the t-test result P < 0.05; P = 0.0265 for the Yale database and P = 0.0186 for the CASIA database.
The proposed face recognition technique is performed in three phases, feature extraction by PCA, adaptive acceleration particle swarm optimization (AAPSO), and parameters selection for SVM with AAPSO.