… the impact of similarity measures integration with ML models, this work makes three major
contributions: (1) proposing newly-integrated models and presenting benchmarking studies …

… The deep neural network model was then used to classify … family classification model
based on deep learning that uses … To better learn the call relation and timing relation between …

… In this paper, we propose a sentence similarity computation model … over using the convolutional
neural network to model sentences to … [43] proposed a model based on the Attention of …

… random field (CRF) enhanced graph convolution network to capture the semantic … for
sequence modeling. It is known that can be benefited from Convolution Neural Networks (CNNs) of …

… For this reason, an RNN-Capsule that is a capsule model based on Recurrent Neural Network
(… Indeed, the model shows a better accuracy when we have more training data. Therefore, …

… of traditional algorithms, deep learning models, including Convolution Neural Network (CNN) …
of ConvBiLSTM was improved by 2.62% better than CNN model, 4.56% better than LSTM …

… neural network is a new model based on the LSTM neural … The basic structure of a
convolutional neural network is shown … the fusion network model in this paper can obtain better …

… system based on deep learning. Our proposed system utilizes a self-attention deep neural
network (SA-DNN) model … to gain a better understanding of the data. Furthermore, thier work is …

… to deep and multi-layer models. The ML models based on probabilistic, neural networks and
others … Interestingly, the pizza enrichment results shown in Table 9.6 are better than security …

… network intrusions. A novel approach using a hybrid algorithm of Convolutional Neural
Network … ) is introduced in this paper to provide improved intrusion detection. This bidirectional …