تقرير
Deep Autoencoder Model Construction Based on Pytorch
| العنوان: | Deep Autoencoder Model Construction Based on Pytorch |
|---|---|
| المؤلفون: | Pan, Junan, Zhao, Zhihao |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Machine Learning |
| الوصف: | This paper proposes a deep autoencoder model based on Pytorch. This algorithm introduces the idea of Pytorch into the auto-encoder, and randomly clears the input weights connected to the hidden layer neurons with a certain probability, so as to achieve the effect of sparse network, which is similar to the starting point of the sparse auto-encoder. The new algorithm effectively solves the problem of possible overfitting of the model and improves the accuracy of image classification. Finally, the experiment is carried out, and the experimental results are compared with ELM, RELM, AE, SAE, DAE. Comment: 16 pages, 10 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2208.08231 |
| رقم الأكسشن: | edsarx.2208.08231 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |