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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...
Crop classification is an important task in many crop monitoring applications. Satellite remote sensing has provided easy, reliable, and fast approaches to crop classification task. In this study, a c...
Graph based semi-supervised classification method are widely used for hyperspectral image classification. We present a couple graph based label propagation method, which contains both the adjacency gr...
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 presented experiment investigates the potential of Multispectral Laser Scanning (MLS) point clouds for single tree species classification. The basic idea is to simulate a MLS sensor by combining t...
Semantic segmentation is a fundamental research in remote sensing image processing. Because of the complex maritime environment, the classification of roads, vegetation, buildings and water from remot...
Individual tree species classification can be done using Light Detection and Ranging (LIDAR) and aerial multichannel images simultaneously. LIDAR is typically used to derive shape features and aeria...
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...
This paper presents a new application of a data-clustering algorithm in Landsat image classification, which improves on conventional classification methods. Neural networks have been widely used in ...
Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. New algorithms have been developed for hyperspectral data classificat...
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...
Airborne laser scanner technique provides a 3D perception of the terrestrial topography, including true ground and objects belonging either to vegetated areas or to human made features. The high intr...
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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