Understanding deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras This jupyter notebook reassembles the code of this article It also contains a trained CNN model, so ...

In this study, we perform land use classification (LUC) using sequences of multispectral Sentinel-2 images taken over multiple years. It evaluates the convolutional neural network (CNN) applied in ...

Mixture of Experts on Convolutional Neural Network Mixture of experts is a ensemble model of neural networks which consists of expert neural networks and gating networks. The expert model is a series ...

Land-Use detection is an important application in the context of remote sensing. This objective is to classify, a chunk of a satellite or high-earth orbit image of the earth, as the type of land-use.

If you’ve dug into any articles on artificial intelligence, you’ve almost certainly run into the term “neural network.” Modeled loosely on the human brain, artificial neural networks ...

Here we show how initially fully connected neural networks solving a discrimination task can learn a convolutional structure directly from their inputs, resulting in localized, space-tiling receptive ...

In machine learning, Convolutional Neural Networks (CNN or ConvNet) are complex feed forward neural networks. CNNs are used for image classification and recognition because of its high accuracy. It ...