A novel CNN+LSTM classification model based on fashion-MNIST

Yaran Ji

doi:10.1117/12.2639667

15 July 2022 A novel CNN+LSTM classification model based on fashion-MNIST

Yaran Ji

Proceedings Volume 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022); 122580S (2022) https://doi.org/10.1117/12.2639667
Event: International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 2022, Qingdao, China

Abstract

Nowadays, Convolutional Neural Network (CNN) based image recognition is a popular research direction. This study uses the Fashion-Mnist dataset, which is more challenging than the Mnist dataset. aims to add Long short-term memory (LSTM) to the structure of CNN to create a hybrid model of CNN and LSTM, called CNN+LSTM model. This model is used to complete and optimize the image classification problem on Fashion-Mnist dataset. The final image classification accuracy of the obtained model is 91.36%, which still needs to be improved, but the accuracy results are better compared to the accuracy of other models.

Citation Download Citation

Yaran Ji "A novel CNN+LSTM classification model based on fashion-MNIST", Proc. SPIE 12258, International Conference on Neural Networks, Information, and Communication Engineering (NNICE 2022), 122580S (15 July 2022); https://doi.org/10.1117/12.2639667

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