Titlebook: AI Technologies and Virtual Reality; Proceedings of 7th I Kazumi Nakamatsu,Srikanta Patnaik,Roumen Kountchev Conference proceedings 2024 Th

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Medicometry and Regional Devlopmentict crime risk levels. The models were meticulously validated using cross-validation techniques and evaluated based on diverse performance metrics. In a bid to further advance our predictive capabilities, we leveraged deep learning techniques with TensorFlow, enabling a performance comparison agains

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Applied Geography: Overview and Introductionment such as analysis and monitoring of traffic congestion. A regression-based model has been proposed to identify and predict the locations for traffic congestion. The model is validated considering a particular road segment in the study area using a geospatial analysis based on geographic informat

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Richard G. Boehm,James D. Harrisonach is able to accurately detect landmarks despite variation in the appearance of the cleft. Further, we show the significant improvement ROI warp has on the prediction of anthropometric landmarks used for cleft surgeries. We collaborate closely with reputed craniofacial surgeons to build our traini

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Homilies for Applied Geographers as the largest at 70 and 120?cm, followed by the supine and prone posture, and upright posture was perceived as the smallest at 220 and 270?cm, followed by the supine and prone posture. This suggests that the upright posture is the most sensitive to eye-height information in size estimation, follow

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Andreas K??b,Regula Frauenfelder,Iris Sossnas. Multivariate non-normality was respected in all statistical analyses. The feasible generalized least squares regressions with the within effect of time showed significant results for the prediction of cybersickness ratings during VR exposure, but not for the comparison before and after VR. The fi

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