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Smart city article details

Title	Optimized Outdoor Parking System For Smart Cities Using Advanced Saliency Detection Method And Hybrid Features Extraction Model
ID_Doc	40742
Authors	Mago N.; Mittal M.; Bhimavarapu U.; Battineni G.
Year	2022
Published	Journal of Taibah University for Science, 16, 1
DOI	http://dx.doi.org/10.1080/16583655.2022.2068325
Abstract	As a new concept in urban development, smart cities are characterized primarily by their mobility. To solve these problems, it became necessary to develop an intelligent system. Using the Advanced Saliency Detection Method and an Efficient Features Extraction Model, the proposed work is aimed at detecting vacant outdoor parking lots. Experimental work has been conducted using the publicly available “PKLot” dataset, which consists of 695,899 segmented images. Under different weather conditions, the images were taken from three different camera locations in two different parking lots in Brazil, including sunny, cloudy, and rainy days. The experimental results mentioned that the hybrid feature extraction model enhanced the performance of parking detection systems. Using three different datasets, PUCPR, UFPR04, and UFPR05, we obtain an accuracy of 99.93%, 99.89%, and 99.87%. This is clear that the hybrid feature extraction model with the PUCPR dataset has produced the highest accuracy. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords	classification; feature extraction; hybrid feature extraction model; parking system; pre-processing; Smart cities

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