… provide effective flood prevention information by integrating the predicted … deep learning
method. Proposed model is based on 3D Convolution Neural Network, the established network …

… Deep neural network is a hot spot of artificial intelligence, which can deal with high-… This
paper presents a DNFS (Deep neural fuzzy system) based on ANFIS (Adaptive network based …

… Word2vec, a language model of neural network, is used to … convolutional neural network.
On the basis of extracting abstract features, network training and prediction of text information …

… We introduce the use of a deep convolutional neural network (CNN) on raw EEG samples
for supervised learning of sleep stage prediction, which does not require any signal …

… In this study, the data has been processed, and the improved convolutional neural network
algorithm (CNN-EI) was used to perform data mining on the dataset of diabetic case data. …

… Deep learning stack machine model in automatic encoding (Stack Auto-Encoder SAE) can
… in nonlinear information, and convolutional neural network (Convolutional Neural Network, …

Automatic image annotation is becoming increasingly important in order to develop
algorithms that are able to search and browse large-scale image databases. In this paper, we …

… network and propose an action recognition model based on multilayer recurrent neural
network… Our model uses three-dimensional pyramid dilated convolution network to process serial …

… We explored the influence of the amount of parameters in different layers of two deep learning
models, convolutional neural network (CNN) and recurrent convolutional neural network (…

… 为了进一步提高预测精度,本文提出了一种将卷积神经网络(convolutional neural network, CNN)与
LSTM相结合的混合深度学习神经网络框架.使用电子健康档案中真实数据集的研究结果表明, …