Detection and classification of public security threats in the Philippines using neural networks
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies
First Page
320
Last Page
324
Publication Date
3-1-2020
Abstract
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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Digitial Object Identifier (DOI)
10.1109/LifeTech48969.2020.1570619075
Recommended Citation
Guillermo, M., Tobias, R., De Jesus, L., Billones, R., Sybingco, E., Dadios, E. P., & Fillone, A. (2020). Detection and classification of public security threats in the Philippines using neural networks. LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies, 320-324. https://doi.org/10.1109/LifeTech48969.2020.1570619075
Disciplines
Manufacturing
Keywords
Electronic surveillance; Neural networks (Computer science); Closed-circuit television; Human security
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