Results 11 to 20 of about 12,913,193 (172)
Classification techniques for hyperspectral remote sensing [PDF]
, 2011 This study concerns with classification techniques in high dimensional space such as that of Hyperspectral Imaging (HSI) data sets, with objectives of understanding the strength and weakness of various classifiers and at the same time to study how ...
Kam, Firmin
core +7 more sources
Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing [PDF]
, 2014 As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral ...
Han, Junwei +6 more
core +4 more sources
Effective classification of Chinese tea samples in hyperspectral imaging [PDF]
, 2013 Maximum likelihood and neural classifiers are two typical techniques in image classification. This paper investigates how to adapt these approaches to hyperspectral imaging for the classification of five kinds of Chinese tea samples, using visible light ...
Ren, Jinchang +2 more
core +4 more sources
Singular spectrum analysis for effective feature extraction in hyperspectral imaging [PDF]
, 2014 As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise ...
Zabalza, Jaime +4 more
core +4 more sources
Remote Sensing, 2020 Hyperspectral image (HSI) classification has become one of the most significant tasks in the field of hyperspectral analysis. However, classifying each pixel in HSI accurately is challenging due to the curse of dimensionality and limited training samples.
Yunhao Zou +3 more
doaj +1 more source
Journal of Spectral Imaging, 2022 Hyperspectral imaging (HSI) is a popular mode of remote sensing imaging that collects data beyond the visible spectrum. Many classification techniques have been developed in recent years, since classification is the most crucial task in hyperspectral ...
Tatireddy Subba Reddy +1 more
doaj +1 more source
Diseases of the Esophagus, 2022 Abstract Background and aim Digital pathology will revolutionize the discriminate of malignant and non-malignant cells in histologically specimens. Hyperspectral imaging (HSI), a new technology combing imaging with spectroscopy might be beneficial for tumor cell identification.
M Maktabi +6 more
openaire +1 more source
Segment-Based Clustering of Hyperspectral Images Using Tree-Based Data Partitioning Structures
Algorithms, 2020 Hyperspectral image classification has been increasingly used in the field of remote sensing. In this study, a new clustering framework for large-scale hyperspectral image (HSI) classification is proposed.
Mohamed Ismail, Milica Orlandić
doaj +1 more source
Remote Sensing, 2022 In recent years, convolutional neural networks (CNNs) have been widely used in hyperspectral image (HSI) classification. However, feature extraction on hyperspectral data still faces numerous challenges.
Jun Sun +6 more
doaj +1 more source
Diseases of the Esophagus, 2022 Abstract Hyperspectral imaging (HSI), as recently applied in medicine, is a novel technology combining imaging with spectroscopy. It might be used to identify, classify and discriminate malignant and non-malignant cells of histopathologic specimens.
Marianne Maktabi +6 more
openaire +1 more source