Perceptual Low-Rank Learning and Geometry-Preserving Feature Selection for Categorizing High-Resolution Aerial Photos

Perceptual Low-Rank Learning and Geometry-Preserving Feature Selection for Categorizing High-Resolution Aerial Photos

Recognizing the multiple categories of an high-resolution (HR) aerial photos is an indispensable technique in geoscience and remote sensing. In this work, a perceptual low-rank algorithm combined with a geometry-preserving feature selection (FS) is proposed for categorizing HR aerial photos. In prac...

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Bibliographic Details
Main Authors: Junwu Zhou, Fuji Ren
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Feature selection
geometry
high-resolution
low-rank
Online Access:https://ieeexplore.ieee.org/document/10274965/

Internet

https://ieeexplore.ieee.org/document/10274965/

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