2026-10-24T10:20:15Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/00007754 2021-12-13T00:38:14Z 1582963674932 1582963674932:1597396989070 user-miit

Audio Event Classification in Threatening Conditions at Surveillance System using Genetic Regulatory Network Tin Ei Kyaw The threatening environments in acoustic surveillance system at important public places in a noisy environment deals with audio events detection is essential and useful application. At surveillance systems aiming to detect abnormal situations based on visual clues while, in some situations, it may be easier to detect and classify events using the audio information. Audio events classification for threatening environment through Genetic Regulatory Network (GRN) is considered. GRN is adopted as classification framework and greatly reduced input dimensions. Thus using the results from GRN framework as inputs for Support Vector Machine (SVM) can correctly classify audio events such as gunshot and explosion with low computational time and complexity. SVM applies as novel discriminative approach for dissimilarity measure in order to address a supervised sound-classification task. Selecting GRN in event detection system can not only reduces cost and effort but also aims to obtain high performance and accuracy in varying nature of environments. 2011-09-09 http://hdl.handle.net/20.500.12678/0000007754 https://meral.edu.mm/records/7754