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Classification techniques for hyperspectral remote sensing [PDF]
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 +6 more sources
Monitoring the Spatiotemporal Distribution of Invasive Aquatic Plants in the Guadiana River, Spain
Monitoring the spatiotemporal distribution of invasive aquatic plants is a challenge in many regions worldwide. One of the most invasive species on Earth is the water hyacinth.
Elena C. Rodriguez-Garlito +2 more
doaj +1 more source
Quality criteria benchmark for hyperspectral imagery [PDF]
Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel +2 more
core +1 more source
THE DETECTION OF CONCEALED TARGETS IN WOODLAND AREAS USING HYPERSPECTRAL IMAGERY [PDF]
Recent innovations in microelectronic and semiconductor technology enable the creation of smaller and economical hyperspectral cameras. A filter combined camera with advanced scanning module is a game changer that extends the application of miniature ...
S. A. Rodriguez Gonzalez +6 more
doaj +1 more source
In this article the author reviews José Bioucas-Dias' key contributions to hyperspectral unmixing (HU), in memory of him as an influential scholar and for his many beautiful ideas introduced to the hyperspectral community. Our story will start with vertex component analysis (VCA) -- one of the most celebrated HU algorithms, with more than 2,000 Google ...
openaire +2 more sources
Joint Bayesian Endmember Extraction and Linear Unmixing for Hyperspectral Imagery [PDF]
This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing ...
Moussaoui, Saïd +10 more
core +1 more source
Singular spectrum analysis for effective feature extraction in hyperspectral imaging [PDF]
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
Editorial for Special Issue “Advances in Hyperspectral Data Exploitation”
Hyperspectral imaging (HSI) has emerged as a promising, advanced technology in remote sensing and has demonstrated great potential in the exploitation of a wide variety of data.
Chein-I Chang +8 more
doaj +1 more source
Customizing kernel functions for SVM-based hyperspectral image classification [PDF]
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms.
Damper, R. I. +7 more
core +2 more sources
Hyperspectral Inverse Skinning
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
openaire +3 more sources

