{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T00:36:46Z","timestamp":1705106206012},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684802","type":"print"},{"value":"9781643684819","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:00:00Z","timestamp":1705017600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,12]]},"abstract":"<jats:p>Distributed Acoustic Sensing (DAS) is a novel technology has been widely applied in pipeline monitoring, railway safety monitoring, perimeter security, and other field. In particular, an effective algorithm for classing events is of the most importance. In our work, a method for event recognition based on convolution neural network is proposed. This method only used raw temporal-spatial signal data into gray scale image for the input of CNN. In order to recognize vibration events quickly and accurately, a small Convolutional neural network structure is proposed. Field experiment results show that our approach can achieve 96.32% classification accuracy and a 0.46 second recognition speed under 1200m distance length of optical fiber cable.<\/jats:p>","DOI":"10.3233\/faia231221","type":"book-chapter","created":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T12:56:20Z","timestamp":1705064180000},"source":"Crossref","is-referenced-by-count":0,"title":["An Event Recognition Method for Distributed Acoustic Sensing Based on Convolutional Neural Network"],"prefix":"10.3233","author":[{"given":"Xiehao","family":"Chen","sequence":"first","affiliation":[{"name":"School of Software, Xinjiang University, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Electronics, Communications and Networks"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA231221","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T12:56:21Z","timestamp":1705064181000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA231221"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,12]]},"ISBN":["9781643684802","9781643684819"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia231221","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,12]]}}}