Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great abundance of information; such a resource, however, poses many challenges in the analysis and interpretation of these data. Deep learning approaches certainly offer a great variety of opportunities for solving c...
Main Authors: | Alberto Signoroni, Mattia Savardi, Annalisa Baronio, Sergio Benini |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/5/5/52 |
Similar Items
-
Classification of Arsenic Bearing Minerals Using Hyperspectral Imaging and Deep Learning for Mineral Processing
by: Natsuo OKADA, et al.
Published: (2021-01-01) -
Hyperspectral image super resolution using deep internal and self‐supervised learning
by: Zhe Liu, et al.
Published: (2024-02-01) -
An Unsupervised Deep Hyperspectral Anomaly Detector
by: Ning Ma, et al.
Published: (2018-02-01) -
Hyperspectral Image Denoising With Dual Deep CNN
by: Wei Shan, et al.
Published: (2019-01-01) -
Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning
by: Martina De Landro, et al.
Published: (2021-10-01)