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• W2897558504 abstract "Augmented Reality (AR) is investigated as a unique technology to combine virtual and real world together. The key feature of AR is to demonstrate extra information in the field of view for those who interact with the authentic environment. Using AR in education setting helps students to engage in genuine exploration in the real world. In this regard, remote laboratories provide a special platform for AR technology to bridge the gap between theoretical and empirical knowledge. For revealing auxiliary data, object tracking scheme plays an imperative role to make visible invisible issue. In this scheme, Particle Swarm Optimization algorithm (PSO) is one of the most famous algorithm in linear and non-linear object tracking by particular identification of target. Contrary to other modified PSO, Elevated-PSO is adopted to improve diversity of particles when all particles are restricted close to the best predicted solution with the enough similarity. This proposed algorithm regarding to target tracking in AR remote labs can fulfill better solutions in comparison with classic and other improved PSO." @default.
• W2897558504 created "2018-10-26" @default.
• W2897558504 creator A5044200395 @default.
• W2897558504 creator A5049130766 @default.
• W2897558504 date "2018-07-01" @default.
• W2897558504 modified "2023-09-29" @default.
• W2897558504 title "Augmented Reality for Remote Laboratory Improving Educational Learning: Using Elevated Particle Swarm Optimization in Object Tracking Scheme" @default.
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• W2897558504 doi "https://doi.org/10.1109/ijcnn.2018.8489685" @default.
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