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Semantic Segmentation in Satellite Hyperspectral Imagery by Deep Learning
Jon Alvarez Justo
, Alexandru Ghita
, Daniel Kovac
, Joseph L. Garrett
, Mariana Iuliana Georgescu
,
Jesus Gonzalez-Llorente
, Radu Tudor Ionescu
, Tor Arne Johansen
Norwegian University of Science and Technology
University of Bucharest
Brno University of Technology
Department of Aerospace Engineering
Research output
:
Contribution to journal
›
Journal Article
›
peer-review
13
Citations (Scopus)
Overview
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Keyphrases
Deep Learning
100%
Semantic Segmentation
100%
Vision Transformer
100%
Hyperspectral
100%
Ground Hyperspectral Data
100%
2D CNN
66%
Deep Learning Model
33%
Effective Solutions
33%
Satellite Data
33%
State-of-the-art Models
33%
Convolutional Neural Network
33%
Compact Size
33%
U-Net
33%
Superior Performance
33%
Convolutional Neural Network Model
33%
Spatial Data
33%
Spectral Information
33%
High-dimensional Feature Space
33%
Model Size
33%
Small Animal Model
33%
Spectral Features
33%
Operation Optimization
33%
Apple
33%
Multi-class Segmentation
33%
Neural Transformer
33%
Satellite Operations
33%
Space Deployment
33%
EO-1
33%
Hyperspectral Mission
33%
Cloud Segmentation
33%
Mobile Inference
33%
1D Convolutional Neural Network (1D CNN)
33%
Fast Inference
33%
Onboard AI
33%
Remote Sensing Applications
33%
Sea-land Segmentation
33%
Orbit Deployment
33%
Computer Science
Deep Learning Method
100%
Image Segmentation
100%
Convolutional Neural Network
100%
Vision Transformer
75%
Effective Solution
25%
Case Study
25%
Spatial Information
25%
Deep Learning Model
25%
Neural Network Model
25%
Superior Performance
25%
Artificial Intelligence
25%
Spectral Information
25%
Dimensional Feature Space
25%
Spectral Feature
25%
Hyperspectral Data
25%
Earth and Planetary Sciences
State of the Art
100%
Artificial Intelligence
100%
Remote Sensing Application
100%
Deep Learning Model
100%
Autonomy
100%