Abandoned Object Detection Method Using Convolutional Neural Network

Saluky, Saluky (2020) Abandoned Object Detection Method Using Convolutional Neural Network. 2020 International Conference on ICT for Smart Society (ICISS). ISSN 2640-0545

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Abstract

Automatic surveillance is an effort to detect anomalies that occur in the surrounding environment such as stations, offices and other public spaces. One of the anomalies that occur is neglected objects. Abandoned objects will become annoying or dangerous if left unattended. Abandoned object detection process begins by detecting a stationary object using Gaussian mixture models, then abandoned recognize objects using a convolutional neural network. The recognition of stage objects is very helpful in determining the bounding box of objects that are left behind, thereby reducing the bias arising from shadows or lighting changes. The resulting effective method to detect abandoned objects and recognize it.

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Item Type:	Article
Subjects:	T Technology > Information Technology
Divisions:	Fakultas Ilmu Tarbiyah dan Keguruan > 4. Tadris Matematika
Depositing User:	Saluky
Date Deposited:	11 Jan 2021 02:31
Last Modified:	11 Jan 2021 02:41
URI:	http://repository.syekhnurjati.ac.id/id/eprint/4147

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