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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...
Remote sensing techniques provide efficient and cost-effective approach to monitor the expansion of built-up area, in comparison to other traditional approaches. For extracting built-up class, one of ...
Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classi...
The study chooses the standard stripe and dual polarization SAR images of GF-3 as the basic data. Residential areas extraction processes and methods based upon GF-3 images texture segmentation are com...
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...
Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, su...
International Symposium on Multispectral Image Processing and Pattern Recognition(MIPPR) is an international academic conference orgnized by the international society for Optical Engineering (SPIE) an...
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...
Recently, hyperspectral image analysis has obtained successful results in information extraction for earth remote sensing system. The data produced with this type of analysis is an important compone...
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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