This project demonstrates the implementation of a Convolutional Neural Network (CNN) for image classification using the CIFAR-10 dataset. The model is built using the MobileNet architecture, which is ...

Image classification has become ... it was named VGG-19. This model was proposed to reduce the number of parameters in a convolutional neural network with improved training time. Below is the block ...

VGG, ResNet, and other deep CNN models have achieved great success in image classification. The pre-trained deep CNN model has been fully trained on a large image dataset (ImageNet), allowing many ...

Abstract: The availability of structural image ... classification performance. We perform extensive experiments on standard structural picture datasets to showcase the efficacy of our suggested ...

This project implements an Image Classification system using a Convolutional Neural Network (CNN). The system takes an input image, processes it through the CNN model, and classifies it into ...

Abstract: Convolutional Neural Networks (CNNs) are particularly precise in several fields, especially computer vision where image classification ... us to reduce the model and deploy it in embedded ...