期刊名称：International Journal of Image, Graphics and Signal Processing
印刷版ISSN：2074-9074
电子版ISSN：2074-9082
出版年度：2021
卷号：13
期号：1
页码：28-39
DOI：10.5815/ijigsp.2021.01.03
出版社：MECS Publisher
摘要：The present study, the main idea of which was based on one of the questions of I.P.T.2018 competition, aimed to develop a high-precision relationship between the fluid temperature and the sound produced when colliding with different surfaces, by creating a data collection tool. In fact, this paper was provided based on a traditional phenomenological project using the well-known deep neural networks, in order to achieve an acceptable accuracy in this project. In order to improve the quality of the paper, the data were analyzed in two ways: I. Using the images of data spectrogram and the known V.G.G.16 network. II. Applying the data audio signal and a convolutional neural network (C.N.N.). Finally, both methods have obtained an acceptable precision above 85%.
关键词：Fluid temperature; data spectrogram; V.G.G.16 (Visual Geometry Group); C.N.N (Convolutional Neural Network).; the environmental sounds; sound classification; physical-computational research; Deep learning
