Convolutionary Neural Network Approach for Aircraft Noise Detection

被引：0

作者：

Pak, Ju-won ^{[1
]}

Kim, Min-koo ^{[1
]}

机构：

[1] Ajou Univ, Dept Software, Suwon, South Korea

来源：

2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (ICAIIC 2019) | 2019年

关键词：

Aircraft noise detection; Convolutional Neural Network; deep learning;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

People living near the airport are experiencing many inconveniences due to frequent aircraft noise. For these people, the government uses the aircraft noise evaluation unit (e.g., Lden) to calculate the degree of annoyance and then compensate for aircraft noise. Aircraft noise evaluation unit should be calculated only by aircraft noise, but the reality is not so. This is because the aircraft noise monitor measures not only aircraft noise but also loud background noise. Therefore, in this paper, we propose a method of recognizing only the aircraft noise among the stored noise from the noise monitor to calculate accurate aircraft noise evaluation unit. The proposal uses convolutional neural network, one of the deep learning techniques. Our proposal purposes less than 1% false-positive (FP) or false-negative (FN) rate.

引用

页码：430 / 434

页数：5