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pro vyhledávání: '"Dimensionality estimation"'
Akademický článek
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Akademický článek
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Autor:
Daniele Cerra, Miguel Pato, Kevin Alonso, Claas Köhler, Mathias Schneider, Raquel de los Reyes, Emiliano Carmona, Rudolf Richter, Franz Kurz, Peter Reinartz, Rupert Müller
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2559 (2021)
Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the val
Externí odkaz:
https://doaj.org/article/de27b5cb690844d2af4f8390a5e80cde
Publikováno v:
ARTIFICIAL INTELLIGENCE
Artificial Intelligence
Artificial Intelligence
The intrinsic nature of noisy and complex data sets is often concealed in low-dimensional structures embedded in a higher dimensional space. Number of methodologies have been developed to extract and represent such structures in the form of manifolds
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::df5c3998d24f5c6e224fd57aabcdc057
https://biblio.ugent.be/publication/8719615
https://biblio.ugent.be/publication/8719615
Publikováno v:
Industrial & Engineering Chemistry Research. 58:5579-5587
By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP-MLE (orthogonal locality preserving projection-maximum likelihood estimation), is introduced for process m
Autor:
Müller, Daniele Cerra, Miguel Pato, Kevin Alonso, Claas Köhler, Mathias Schneider, Raquel de los Reyes, Emiliano Carmona, Rudolf Richter, Franz Kurz, Peter Reinartz, Rupert
Publikováno v:
Remote Sensing; Volume 13; Issue 13; Pages: 2559
Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the val
Autor:
Cerra, Daniele, Pato, Miguel, Alonso, Kevin, Köhler, Claas, Schneider, Mathias, de los Reyes, Raquel, Carmona, Emiliano, Richter, Rudolf, Kurz, Franz, Reinartz, Peter, Müller, Rupert
Publikováno v:
Remote Sensing, Vol 13, Iss 2559, p 2559 (2021)
Spectral unmixing represents both an application per se and a pre-processing step for several applications involving data acquired by imaging spectrometers. However, there is still a lack of publicly available reference data sets suitable for the val
Autor:
Paolo Brambilla, Niccolò Zovetti, Marcella Bellani, Nicola Dusi, Cinzia Perlini, Elisa Ciceri, Pietro Bontempi, Veronica Marinelli, Letizia Squarcina, Giada Zoccatelli, Maria Gloria Rossetti, Andrea Sbarbati, Franco Alessandrini
Publikováno v:
Bipolar disordersReferences. 22(6)
Objectives Bipolar disorder (BD) is a psychiatric condition causing shifts in mood, energy and activity levels severely altering the quality of life of the patients even in the euthymic phase. Although widely accepted, the neurobiological bases of th
Autor:
Aiqing Xu, Xiaorong Wang
Publikováno v:
Sankhya B. 81:123-132
Intrinsic dimensionality estimation plays a pivotal role in dealing with high-dimensional datasets. In this work, we aim to develop a robust dimensionality estimation algorithm by investigating the intrinsic dimensionality estimation methods for data