Satellite Image Classification using Deep Learning Comparison of multiple CNN architectures (CNN, VGG16, ResNet34, ResNet50, InceptionV3) for satellite image classification.

As a new optical machine learning framework, the diffractive deep neural network (D2NN) has attracted much attention due to its advantages such as low power consumption, parallel computing, and fast ...

Convolutional neural networks (CNNs) are highly effective deep learning architectures for remote sensing (RS) image classification. However, the interpretability of CNN architecture remains ...

The proposed deep-learning algorithm detects three different diseases from features extracted from Optical Coherence Tomography (OCT) images. The deep-learning algorithm uses CNN to classify OCT ...

Convolutional Neural Network (CNN) has made outstanding achievements in image processing and detection. The recent research uses CNN to classify the medical images, but this performance depends on its ...

In this comprehensive review, we explore potential interdisciplinary approaches for early detection and provide insight into recent advances on AD classification using 3D CNN architectures for ...