SIMULTANEOUS LOCALIZATION AND MAPPING WITH ITERATIVE SPARSE EXTENDED INFORMATION FILTER FOR AUTONOMOUS VEHICLES

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles.The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors.With the hair cuttin

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Blows or Falls? Distinction by Random Forest Classification

In this study, we propose a classification method between falls and blows using random forests.In total, 400 anonymized patients presenting with fractures from falls or blows aged between 20 and 49 years old were used.There were 549 types of fractures for 57 bones and 12 anatomical regions observed.We first Body Wear tested various models according

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