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  • Economics  (2)
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  • Economics  (2)
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  • 1
    Online Resource
    Online Resource
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-10-11), p. 1-10
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-10-11), p. 1-10
    Abstract: Aiming at the demand of industrial instrument reading, this study proposes a method of industrial instrument classification and reading recognition based on YOLOv3. Given that industrial meters can be divided into pointer meters and digital meters according to the dial type, this method conducts a reading study for each of the two types of meters. Firstly, the YOLOv3 model is trained to recognize and detect the meter types and classify the meters according to the values of the obtained classes. The pointer meter uses a Hough circle to detect the dial, extracts the scale and the pointer, calculates the angle between the 0 scale line and the pointer, and obtains the reading of the pointer meter. The digital meter extracts the digits by finding the contours of the dial and the digit area and then uses a support vector machine (SVM) to identify the extracted digits and output the readings of the digital meter. Through the test, the mean average precision (mAP) of the recognition model in this study is 93.73%. The absolute error of pointer meter reading is less than 0.1 in general, and the maximum relative error is 0.35%. The accuracy of the digital meter reading is 99.7%. The proposed method can accurately read the value of the instrument and meet the needs of industrial production.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    RVK:
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-9-22), p. 1-9
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-9-22), p. 1-9
    Abstract: With the emergence of more and more new music styles, Guzheng, a traditional national musical instrument that has been handed down for thousands of years, also faces new challenges. However, with the development of the times and aesthetics, composers have created various modern Guzheng music, thus injecting new vitality into the development of Guzheng. In order to study the mutual conversion between Guzheng music and other music, this paper proposes a Guzheng music conversion model based on Star generative adversarial networks (GAN), which can convert any length of music and realize the music conversion between various styles. Based on the idea of star GAN, this model uses Mel spectrum of music and random target style tags to train a general generator to generate a specified music style. It is found that the model proposed in this paper has better conversion effect between similar styles of music; that is, when Guzheng music is converted into pop and flute, the effect is the best, the average accuracy is 89.62% and 90.32%, respectively, and the cosine similarity is also 15.8 and 20.5.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    RVK:
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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