머신러닝을 이용한 탄성파 해양학 자료 잡음 억제

DC Field Value Language
dc.contributor.author 전형구 -
dc.contributor.author 주형태 -
dc.contributor.author 이상훈 -
dc.contributor.author 문혜진 -
dc.contributor.author 전청균 -
dc.contributor.author 안신혜 -
dc.date.accessioned 2020-07-01T03:18:27Z -
dc.date.available 2020-07-01T03:18:27Z -
dc.date.created 2020-02-11 -
dc.date.issued 2019-12-12 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/21027 -
dc.description.abstract Seismic oceanography (SO) is a method of obtaining the structure and physical properties of ocean by using the seismic exploration and processing. The advantage of the SO is that the data acquired by using SO has higher lateral resolution than the data acquired by using the conventional oceanographic devices. Therefore, the SO has been used to study the distribution of the water mass, the dissipation of the turbulence, and characteristic of the internal waves in many regions. In most SO studies, the seismic data was obtained by using the air-gun, but recently the sparker was also used to generate higher frequency source wavelet. The use of the higher frequency components increases the vertical resolution of the seismic data, which can provide much detail information of the ocean. However, the low signal to noise ratio of the sparker seismic data is one of the biggest obstacles of using sparker source in SO study. The energy of the sparker sourceis much smaller than the energy of the air-gun source, thus the influence of the random noise is severer in sparker seismic data than in the air-gun seismic data. Therefore, the attenuation of the random noise in the sparker seismic data is one of the important issues in SO data processing. In this study, we applied convolutional neural network (CNN) to attenuate the random noise in the sparker seismic data. The Denoising Convolutional Neural Network (DnCNN) which extracts th -
dc.description.uri 1 -
dc.language English -
dc.publisher American Geophysical Union -
dc.relation.isPartOf AGU 2019 -
dc.title 머신러닝을 이용한 탄성파 해양학 자료 잡음 억제 -
dc.title.alternative Noise attenuation of the Sparker Seismic Oceanography data using Machine learning -
dc.type Conference -
dc.citation.conferencePlace US -
dc.citation.title AGU 2019 -
dc.contributor.alternativeName 전형구 -
dc.contributor.alternativeName 주형태 -
dc.contributor.alternativeName 이상훈 -
dc.contributor.alternativeName 문혜진 -
dc.contributor.alternativeName 전청균 -
dc.contributor.alternativeName 안신혜 -
dc.identifier.bibliographicCitation AGU 2019 -
dc.description.journalClass 1 -
Appears in Collections:
Ocean Climate Solutions Research Division > Ocean Climate Response & Ecosystem Research Department > 2. Conference Papers
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