The Image Classification using Convolutional Neural Networks (CNN) project demonstrates the application of deep learning techniques for image classification tasks. By training a CNN model on the CIFAR ...

In this article, we will implement the multiclass image classification using the VGG-19 Deep Convolutional Network used as a Transfer Learning framework where the VGGNet comes pre-trained on the ...

This project consists of classifying images of dogs using hybrid Convolutional Neural Network (CNN) and Vision Transformer (ViT). I will be comparing between a pure CNN architecture and a hybrid ar ...

The use of this technique is intended to reduce the problem of overfitting and computational load in the learning process using CNN modeling that was engineered from scratch. The results of this study ...

To solve this problem, the researchers hybridized a CNN with particle swarm optimization (PSO) to find better values for these hyperparameters. PSO was hybridized using genetic algorithm to solve the ...

Training deep learning models without using GPUs can be the difference between waiting a few minutes to waiting hours. Automated Text Classification In order to build predictive models, we need ...

The study found that deep learning models, especially CNNs, were the most frequently implemented technique (61.2%), followed ...