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作者:

Lin, Chen (Lin, Chen.)

收录:

EI Scopus

摘要:

As we know, recently deep learning networks have gained currency for some time under the background of the rise of big model, and it has been widely used for various areas including microbiology images recognition. Nowadays deep learning network models are also divided into many different types, and many new models are proposed every year to achieve better performance. After introducing their specific principles and composition structure, this paper compares three common different deep learning networks named Deep neural network notation (DNN), Convolutional Neural network (CNN) and Recurrent Neural network (RNN), and introduces the recently emerging model named Residual network (Resnet), starting from a specific situation which calls for garbage classification. Moreover, during this experiment, it also gives the method V pipe a try which differs a lot from the former method, and receives good results worth celebrating. © 2023 SPIE.

关键词:

Image classification Learning systems Deep neural networks Convolutional neural networks Microbiology Classification (of information) Recurrent neural networks

作者机构:

  • [ 1 ] [Lin, Chen]Information Security, Beijing University of Technology, Ping le yuan 100, Beijing Province, Beijing; 100000, China

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来源 :

ISSN: 0277-786X

年份: 2023

卷: 12610

语种: 英文

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ESI高被引论文在榜: 0 展开所有

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