Deep learning networks for microbiology images recognition

Chen Lin

doi:10.1117/12.2671439

28 April 2023 Deep learning networks for microbiology images recognition

Chen Lin

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126101W (2023) https://doi.org/10.1117/12.2671439
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

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.

Citation Download Citation

Chen Lin "Deep learning networks for microbiology images recognition", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126101W (28 April 2023); https://doi.org/10.1117/12.2671439

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KEYWORDS

Deep learning

Neural networks

Education and training

Convolution

Data modeling

Image processing

Neurons

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