A New Framework for Evaluating Image Quality Including Deep Learning Task Performances as a Proxy-Reference-Cited by-同舟云学术

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A New Framework for Evaluating Image Quality Including Deep Learning Task Performances as a Proxy

Published:2024 Issue: Volume:17 Page:3285-3296
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Gallés Pau¹^ORCID,Takáts Katalin¹^ORCID,Hernández-Cabronero Miguel²^ORCID,Berga David³^ORCID,Pega Luciano¹^ORCID,Riordan-Chen Laura¹^ORCID,Garcia Clara¹^ORCID,Becker Guillermo¹^ORCID,Garriga Adan³^ORCID,Bukva Anica³^ORCID,Serra-Sagristà Joan²^ORCID,Vilaseca David¹^ORCID,Marín Javier¹^ORCID

Affiliation:

1. Satellogic Inc, Barcelona, Spain

2. Universitat Autònoma de Barcelona - UAB-DEIC-GICI, Bellaterra, Spain

3. EURECAT - Multimedia Technologies Unit, Barcelona, Spain

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10356628.pdf?arnumber=10356628

Reference23 articles.

1. Spaceworks 2014 nano/microsatellite market assessment;Buchen,2014

2. StfNet: A Two-Stream Convolutional Neural Network for Spatiotemporal Image Fusion

3. Effective Pan-Sharpening by Multiscale Invertible Neural Network and Heterogeneous Task Distilling

4. Rethinking Pan-Sharpening in Closed-Loop Regularization

5. Optimizing data processing in space for object detection in satellite imagery;Lofqvist,2021

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