Open AccessAutomatic Cigarette Object Concealment in Video using R-CNN
Author(s) -
Kadek Utari Widiarsini,
Duman Care Khrisne,
I Made Arsa Suyadnya
Publication year - 2021
Publication title -
journal of electrical, electronics and informatics
Language(s) - English
Resource type - Journals
eISSN - 2622-0393
pISSN - 2549-8304
DOI - 10.24843/jeei.2021.v05.i01.p04
Subject(s) - convolutional neural network , lung cancer , nicotine , computer science , artificial intelligence , sample (material) , medicine , computer vision , pathology , psychiatry , chemistry , chromatography
Cigarettes are packaged processed tobacco products, produced from the Nicotiana Tabacum, Nicotiana Rustica plants and other species or synthetics that contain nicotine with or without additives. Smoking is known to the public as one of the causes of death in the world that is quite large such as asthma, lung infections, oral cancer, throat cancer, lung cancer, heart attacks, strokes, dementia, erectile dysfunction (impotence), and so on. This research aims to build an application that can recognize cigarettes automatically and conceal pictures so that people especially minors are not affected by cigarettes. The application is built using the Region-based Convolutional Neural Network (R-CNN) method. The study uses images that have cigarette objects in them. The test is carried out to find out the application performance such as the level of application accuracy in recognizing cigarette objects. Based on the test results with a sample of 126 cigarette images, the application built is able to recognize cigarette objects by obtaining an accuracy value of 63%.