Detection and classification of public security threats in the Philippines using neural networks

Detection and classification of public security threats in the Philippines using neural networks

Life being put into jeopardy when in public has always been Filipinos' concern. While there are reinforcements of laws, and common practices taught, these are no more than just band-aid solutions to the problem. With the immediate detection and classification of common public security threats t...

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Bibliographic Details
Main Authors: Guillermo, Marielet, Tobias, Rogelio Ruzcko, De Jesus, Luigi Carlo, Billones, Robert Kerwin, Sybingco, Edwin, Dadios, Elmer P., Fillone, Alexis
Format: text
Published: Animo Repository 2020
Subjects:
Electronic surveillance
Neural networks (Computer science)
Closed-circuit television
Human security
Manufacturing
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/1740
https://animorepository.dlsu.edu.ph/context/faculty_research/article/2739/type/native/viewcontent
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Institution: De La Salle University
Description
Summary:Life being put into jeopardy when in public has always been Filipinos' concern. While there are reinforcements of laws, and common practices taught, these are no more than just band-aid solutions to the problem. With the immediate detection and classification of common public security threats through the videos fed from CCTVs, it will be an immense help to protect Filipinos. In this study, the use of pre-trained R-CNN model inception v2 alongside tools for other phases such as annotation, training, and testing will be discussed. The process through which the study attained the goal of the system will be highlighted. © 2020 IEEE.

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