It starts with the concept of convolution in two dimensions and its justification for its use in deep learning, after which the structure of a convolutional neural network is described. The training ...

Customer Churn Prediction,Deep Learning Models,Experiments In This Paper,Feature Information,Feature Maps,Local Feature Extraction,Local Spatial Features,Minority Class,Multi-scale ...

You can read more about sound event detection literature here. This method was first proposed in 'Sound event detection using spatial features and convolutional recurrent neural network'. It recently ...

Artificial neural networks (ANN) are computational systems that "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules.

Based on the deep learning method, the convolutional neural network model is used to extract the newly produced 3D feature to ... The conversion formulas of voltage, current and power at each sampling ...

Methods: To address this issue, this paper proposes a fault diagnosis algorithm based on a multi-channel neighbor feature convolutional network ... For the fault diagnosis algorithm based on a neural ...

Taiyuan, Shanxi, China Introduction: In the aviation field, drone search and rescue is a highly urgent task involving ... Small-object detection is a long-term challenge in deep learning convolutional ...