Results 21 to 30 of about 107,679 (337)
HYPERSPECTRAL DATA CLASSIFICATION USING FACTOR GRAPHS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Abstract. Accurate classification of hyperspectral data is still a competitive task and new classification methods are developed to achieve desired tasks of hyperspectral data use. The objective of this paper is to develop a new method for hyperspectral data classification ensuring the classification model properties like transferability ...
Makarau, Aliaksei +3 more
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Auditory Display of Fluorescence Image Data in an In Vivo Tumor Model
Diagnostics, 2022 Objectives: This research aims to apply an auditory display for tumor imaging using fluorescence data, discuss its feasibility for in vivo tumor evaluation, and check its potential for assisting enhanced cancer perception.
Sheen-Woo Lee +3 more
doaj +1 more source
A new kernel method for hyperspectral image feature extraction [PDF]
, 2017 Hyperspectral image provides abundant spectral information for remote discrimination of subtle differences in ground covers. However, the increasing spectral dimensions, as well as the information redundancy, make the analysis and interpretation of ...
Gao, Lianru +3 more
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Hyperspectral Data: Efficient and Secure Transmission [PDF]
Algorithms, 2017 Airborne and spaceborne hyperspectral sensors collect information which is derived from the electromagnetic spectrum of an observed area. Hyperspectral data are used in several studies and they are an important aid in different real-life applications (e.g., mining and geology applications, ecology, surveillance, etc.). A hyperspectral image has a three-
Pizzolante, Raffaele, Carpentieri, Bruno
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Remote Sensing, 2017 Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can ...
Telmo Adão +6 more
doaj +1 more source
Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image [PDF]
, 2017 As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral image (HSI) classification, the recognition rate is too low. This is because
Cao, Faxian +4 more
core +3 more sources
Hyperspectral Data Augmentation
, 2019 Submitted to IEEE Geoscience and Remote Sensing ...
Nalepa, Jakub +2 more
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Power spectral clustering on hyperspectral data [PDF]
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 Classification of remotely sensed data is an important task for many practical applications. However, it is not always possible to get the ground truth for supervised learning methods. Thus unsupervised methods form a valuable tool in such situations. Such methods are referred to as clustering methods. There exists several strategies for clustering the
Challa, Aditya +3 more
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Customizing kernel functions for SVM-based hyperspectral image classification [PDF]
, 2008 Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms.
Baofeng Guo +4 more
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Submerged Kelp Detection with Hyperspectral Data [PDF]
Remote Sensing, 2016 Submerged marine forests of macroalgae known as kelp are one of the key structures for coastal ecosystems worldwide. These communities are responding to climate driven habitat changes and are therefore appropriate indicators of ecosystem status and health. Hyperspectral remote sensing provides a tool for a spatial kelp habitat mapping.
Florian Uhl +2 more
openaire +3 more sources