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Study on the Prediction of Rice Noodle Raw Material Index Content by Deep Feature Fusion

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成果类型:
会议论文
作者:
Tian Z.;Zhou K.;Shen W.;Jin W.;Zhao Q.;...
通讯作者:
Zhou, K.
作者机构:
[Zhou K.; Tian Z.] College of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan, 430023, China
[Shen W.; Jin W.] College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan, 430023, China
[Zhao Q.] Xiangyang Tianyuan Lohas Rice Industry Co. Ltd., Xiangyang, 441022, China
[Li G.] Qianjiang Jujin Rice Industry Co. Ltd., Qianjiang, 433115, China
通讯机构:
[Zhou, K.] C
College of Mathematics and Computer Science, China
语种:
英文
关键词:
Deep feature fusion;Machine learning;Raw material index;Value prediction
期刊:
Communications in Computer and Information Science
ISSN:
1865-0929
年:
2022
卷:
1744 CCIS
页码:
288-304
会议名称:
7th International Conference on Data Mining and Big Data, DMBD 2022
会议时间:
21 November 2022 through 24 November 2022
主编:
Tan Y.Shi Y.
出版者:
Springer Science and Business Media Deutschland GmbH
ISBN:
9789811992964
基金类别:
Acknowledgment. The work of this paper is supported by the subproject of National Key Research and Development Program of China (Grant No. 2017YFD0401102-02)
机构署名:
本校为第一机构
院系归属:
食品科学与工程学院
数学与计算机学院
摘要:
Rice noodle is a special snack in southern China. With the development of the grain industry and the improvement of living standards, choosing the right raw materials to produce high-quality rice noodles has become one of the problems to be solved at present. Therefore, on the premise of satisfying various characteristics of rice noodles, this paper proposed a deep feature fusion method, which combines with machine learning algorithm to achieve the backward prediction of raw material index content of rice noodles. Deep feature fusion can improv...

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