This paper proposes a method based on long short-term memory (LSTM) for supervised classification of encrypted DSM data.
The results show that the data length can be processed is shorten to 10 bytes by processing DSM as one-dimensional time series while the traditional methods ...
This paper proposes a method based on long short-term memory (LSTM) for supervised classification of encrypted DSM data. And for unsupervised classification, ...
Qing Li, Yonghui Ju, Chang Zhao: Classification of Discrete Sequential Protocol Messages Based on LSTM Network and Transfer Learning. ICCCS 2020: 424-430.
Classification of Discrete Sequential Protocol Messages Based on LSTM Network and Transfer Learning. ICCCS 2020: 424-430. [c1]. view. electronic edition via ...
Aug 7, 2022 · In this post, you will discover how you can develop LSTM recurrent neural network models for sequence classification problems in Python using the Keras deep ...
Missing: Protocol | Show results with:Protocol
A two-stage semi-supervised classification method based on Generative Adversarial Networks (GAN) for sparsely labeled encrypted Discrete Sequence Protocol ...
The proposed hybrid models consist of the convolutional neural networks (CNN) and the Long-Short Term Memory (LSTM). ... The transfer learning strategy and data ...
Text Messages Classification using LSTM, Bi-LSTM, and GRU
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Aug 21, 2022 · This article aims to conduct a binary classification model to detect which text messages are spam or not spam (ham).
Missing: Discrete Protocol Transfer
First, we propose a method for successfully utilizing a pretrained sentiment analysis classification model to reduce the test error rate on an emotion ...
Missing: Protocol | Show results with:Protocol