Diverse Capsules Network Combining Multiconvolutional Layers for Remote Sensing Image Scene Classification

Remote Sensing Image Classification

Bayesian Network Classifiers. An Application to Remote Sensing Image Classification

Different probabilistic models for classification and prediction problems are anlyzed in this article studying their behaviour and capability in data classification. To show the capability of Bayesian Networks to deal with classification problems four types of Bayesian Networks are introduced, a General Bayesian Network, the Naive Bayes, a Bayesian Network Augmented Naive Bayes and the Tree Aug...

Remote Sensing Image Analysis via a Texture Classification Neural Network

In this work we apply a texture classification network to remote sensing image analysis. The goal is to extract the characteristics of the area depicted in the input image, thus achieving a segmented map of the region. We have recently proposed a combined neural network and rule-based framework for texture recognition. The framework uses unsupervised and supervised learning, and provides probab...

Adaptive Deep Pyramid Matching for Remote Sensing Scene Classification

Convolutional neural networks (CNNs) have attracted increasing attention in the remote sensing community. Most CNNs only take the last fully-connected layers as features for the classification of remotely sensed images, discarding the other convolutional layer features which may also be helpful for classification purposes. In this paper, we propose a new adaptive deep pyramid matching (ADPM) mo...

A Modified Stochastic Neighbor Embedding for Combining Multiple Features for Remote Sensing Image Classification

In remote sensing image interpretation, it is important to combine multiple features of a certain pixel in both spatial and spectral domains to improve the classification accuracy, such as spectral signature, morphological property, and shape feature. Therefore, it is essential to consider the complementary property of different features and combine them in order to obtain an accurate classific...