Implementation of Malicious Things Detection at Public Places Using Deep Learning
P. Aleemulla Khan1, N. Thirupathi Rao2, Debnath Bhattacharyya3
1P. Aleemulla Khan, Department of Computer Science and Engineering, Vignan’s Institute of Information Technology, Visakhapatnam (Andhra Pradesh), India.
2N. Thirupathi Rao, Department of Computer Science and Engineering, Vignan’s Institute of Information Technology, Visakhapatnam (Andhra Pradesh), India.
3Debnath Bhattacharyya, Department of Computer Science and Engineering, Vignan’s Institute of Information Technology, Visakhapatnam (Andhra Pradesh), India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 2792-2798 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6401058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: To provide effective security in crowded or public areas in today’s world is a big challenge for us. One of the major challenges is to detect or monitor potential threats such as explosive items or bombs (Abandoned luggage items).In this paper we propose an approach for automatic detection of abandoned luggage and alerting the security alliances ,We use deep learning to train the system with a set of images, these images were given to the trained system which is going to visualize the objects in the image and calculate the distance between objects if the object is person and baggage or only baggage. If the distance is greater than a threshold distance limit then the system is going to raise an alarm for the security alliances.
Keyword: Explosive Items, Deep Learning, Security Alliances.
Scope of the Article: Deep Learning