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In this talk, we will introduce some hyperspectral image classification methods based on deep learning architecture. Recently, deep learning-based hyperspectral image classification has attracted more...
Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this applica...
The main objective of this paper is to develop a model which combines in the same process image classification and restoration. Image classification consists of assigning a label to each site of an ...
Competitive learning neural networks have been successfully used as unsupervised training methods. It provides a way to discover the salient general features that can be used to classify a set of pa...
A number of studies have been carried out to find an appropriate spatial resolution to which to aggregate data in order to reduce the variation within an object, and minimize the classification erro...
In this paper a new classification technique for hyperspectral data based on synergetics theory is presented. Synergetics originally introduced by the physicist H. Haken is an interdisciplinary th...
Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learnin...

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