6 天前 - … , including random forests (RF), convolutional neural networks (CNN), XGBoost, DL
[5, 6], … higher-order neural networks (HONNs). This subset of feedforward neural networks …

7 天前 - … a convolutional neural network with a reduced number of layers. More precisely,
it is a classifier based on neural networks that contains four convolutional … of the network is …

7 天前 - … In the context of our research on the detection of lung abnormalities by convolutional
neural networks (CNNs), MAP plays a crucial role in evaluating the effectiveness and …

7 天前 - … Special attention is paid to machine learning algorithms in financial forecasting,
especially neural networks, SVM, and evolutionary methods. With the growing interest of …

8 天前 - … Firstly, spatio-temporal feature mining is conducted, where convolutional neural
networks are employed to learn crucial local features of transient curves, and bidirectional …

8 天前 - … network model integrating a convolutional neural network (CNN) and a bi-directional
long short-term memory network … ) algorithm based on neural network hyperparameters for …

8 天前 - … The proposed model utilizes a hybrid architecture combining convolutional neural
networks (CNNs) and long short-term memory (LSTM) networks to capture both spatial and …

8 天前 - … an Artificial Neural Network (ANN) to represent the … Convolutional Neural
Networks (CNNs) have recently … FlowNet uses a convolutional neural network model to learn …

8 天前 - … in this domain is the Convolutional Neural Network, which … of the Deep Convolutional
Generative Adversarial Networks (… to train a Convolutional Neural Network model for the …

8 天前 - … To extract features from these mixed observations, Convolutional Neural
Networks (CNN) were applied for extracting visual features, and Fully Connected Networks (FCN) …