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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:Deep leaning-based hyperspectral image classification
深度倾斜 高光谱 图像分类
2023/5/4
EXTRACTION OF BUILT-UP AREA BY COMBINING TEXTURAL FEATURES AND SPECTRAL INDICES FROM LANDSAT-8 MULTISPECTRAL IMAGE
Built-up Support Vector Machine Texture
2019/2/28
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 IMAGE DENOISING USING A NONLOCAL SPECTRAL SPATIAL PRINCIPAL COMPONENT ANALYSIS
Hyperspectral Images Noise Reduction Nonlocal Similarity Spectral Spatial Information Principal Component Analysis
2018/5/14
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 OF RESIDENTIAL AREAS EXTRACTION BASED ON GF-3 TEXTURE IMAGE SEGMENTATION
Residential Areas Extraction GF-3, Backscattering Coefficient Image Filtering Texture Feature, Image Segmentation
2018/5/15
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...
A HYPERSPECTRAL IMAGE CLASSIFICATION METHOD USING ISOMAP AND RVM
Hyperspectral Image Classification Manifold Learning Isometric Feature Mapping Support Vector Machines Relevance Vector Machines
2018/5/11
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...
PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON
Python Data analysis Hyperspectral imaging Image processing Machine learning Open source
2018/5/11
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...
10th SPIE International Symposium on Multispectral Image Processing and Pattern Recogniton (MIPPR2017)
10th SPIE International Symposium Multispectral Image Processing and Pattern Recogniton
2017/7/17
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...
A GAMMA-CONVERGENCE APPLIED TO MULTISPECTRAL IMAGE CLASSIFICATION AND RESTORATION
Image Classification Image Restoration Multispectral satellite image Remote Sensing
2015/7/30
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 ...
SUPERVISED AND UNSUPERVISED NEURAL MODELS FOR MULTISPECTRAL IMAGE CLASSIFICATION
Land Cover Classification Identification Algorithms Artificial_Intelligence Imagery Pixel Multispectral
2015/7/29
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...
HYPERSPECTRAL IMAGE ANALYSIS FOR MATERIAL MAPPING USING SPECTRAL MATCHING
Hyper Spectral Imaging Image Analysis Material Mapping Urban Scene Description Data Fusion
2015/7/29
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...
SYNERGETICS FRAMEWORK FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Synergetics hyperspectral image image classification
2014/4/24
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...
SPECTRAL REGRESSION DISCRIMINANT ANALYSIS FOR HYPERSPECTRAL IMAGE CLASSIFICATION
Dimensionality reduction Hyperspectral image classification manifold learning Eigen-decomposition Spectral regression discriminant analysis Embedding function
2014/4/28
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...