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 ...

Many efforts have been made to improve the accuracy of RS scene classification. Scene classification is a challenging problem, especially for large datasets with tens of thousands of images with a ...

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 ...

we can see that the classification effect of the dual-branch CNN network model is the best, and it can play a greater role in the recognition and classification of remote sensing images. CNN can ...

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 ...