Embedded Night-Vision System for Pedestrian Detection using Adaboosta Machine Learning Meta-Algorithm
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Abstract
Operational vision-based strategies for the driver tomaximize human vision's capacity and ensure safe driving.Regrettably, their extensive service is practically limited tohigh-priced automobiles. Rather than the value of hardwareparts,expensiveismostlikelyaderivativeofthepriceacquired during the testing. This project aims to demonstratehow state-of-the-art algorithms can be used to build a mobilesystemforpedestriandetectioninpoor lighting conditions.Weusedacascade object detector to detect human detectioninthermalimageryandfoundthatthefindingswereinconsistentwiththecurrentstateofthedeeplearningapproach.
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SriSaiRishitha, A. P. . (2021). Embedded Night-Vision System for Pedestrian Detection using Adaboosta Machine Learning Meta-Algorithm. Annals of the Romanian Society for Cell Biology, 25(6), 7825–7830. Retrieved from https://annalsofrscb.ro/index.php/journal/article/view/6973
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