A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...

Description Convolutional Neural Networks (CNN) are mainly used for image recognition. The fact that the input is assumed to be an image enables an architecture to be created such that certain ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

A Convolutional Neural Network (CNN) is a form of artificial intelligence that plays a key role in the AI ecosytem due to its ability to analyze and understand visual data. The need to decipher ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch.

Convolutional neural networks (CNNs) are a type of neural network that is designed to capture increasingly more complex features within its input data. To do this, CNNs are constructed from a ...

The learning capability of convolutional neural networks (CNNs) originates from a combination of various feature extraction layers that fully utilize a large amount of data. However, they often ...

Jun Shu, Mingzhou Deng, Juncheng He, Optimization of Ship-borne Anti-collision Sounding System Based on Internet of Things and Full Convolution Neural Network, Journal of Coastal Research, SPECIAL ...