Results 41 to 50 of about 153,077 (360)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Band redundancy and limitation of labeled samples restrict the development of hyperspectral image classification (HSIC) greatly. To address the earlier issues, the classification models such as subspace-based support vector machines, which have gained a ...
Jiaochan Hu +5 more
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Hyperspectral Imaging for Bloodstain Identification [PDF]
Sensors, 2021 Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification can help to confirm a suspect, and for that reason, several chemical methods are used to reconstruct the crime scene however, these methods can affect subsequent DNA analysis. Therefore, this study presents a non-destructive method for bloodstain identification
Maheen Zulfiqar +4 more
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Nonlinear unmixing of hyperspectral images: Models and algorithms [PDF]
, 2013 When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).
McLaughlin, Stephen; id_orcid +14 more
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Band Subset Selection for Hyperspectral Image Classification
Remote Sensing, 2018 This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one ...
Chunyan Yu, Meiping Song, Chein-I Chang
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Nonlinear spectral unmixing of hyperspectral images using Gaussian processes [PDF]
, 2012 This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components ...
Altmann, Yoann +5 more
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Journal of Applied Remote Sensing, 2021 . Hyperspectral imaging has been used in a variety of geological applications since its advent in the 1970s. In the last few decades, different techniques have been developed by geologists to analyze hyperspectral data in order to quantitatively extract ...
S. Peyghambari, Yun Zhang
semanticscholar +1 more source
A New GPU Implementation of Support Vector Machines for Fast Hyperspectral Image Classification
Remote Sensing, 2020 The storage and processing of remotely sensed hyperspectral images (HSIs) is facing important challenges due to the computational requirements involved in the analysis of these images, characterized by continuous and narrow spectral channels.
Mercedes E. Paoletti +4 more
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Hyperspectral Inverse Skinning
Computer Graphics Forum, 2020 AbstractIn example‐based inverse linear blend skinning (LBS), a collection of poses (e.g. animation frames) are given, and the goal is finding skinning weights and transformation matrices that closely reproduce the input. These poses may come from physical simulation, direct mesh editing, motion capture or another deformation rig.
Songrun Liu +3 more
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Classification of Hyperspectral and LiDAR Data Using Coupled CNNs [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2020 In this article, we propose an efficient and effective framework to fuse hyperspectral and light detection and ranging (LiDAR) data using two coupled convolutional neural networks (CNNs).
Renlong Hang +5 more
semanticscholar +1 more source
Fusion of Various Band Selection Methods for Hyperspectral Imagery
Remote Sensing, 2019 This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS.
Yulei Wang +3 more
doaj +1 more source