Deep Learning-Based Single Image Super-Resolution: An Investigation for Dense Scene Reconstruction with UAS Photogrammetry

Deep Learning-Based Single Image Super-Resolution: An Investigation for Dense Scene Reconstruction with UAS Photogrammetry

The deep convolutional neural network (DCNN) has recently been applied to the highly challenging and ill-posed problem of single image super-resolution (SISR), which aims to predict high-resolution (HR) images from their corresponding low-resolution (LR) images. In many remote sensing (RS) applicati...

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Bibliographic Details
Main Authors: Mohammad Pashaei, Michael J. Starek, Hamid Kamangir, Jacob Berryhill
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
unmanned aircraft system (UAS)
deep learning
super-resolution (SR)
convolutional neural network (CNN)
generative adversarial network (GAN)
structure-from-motion
Online Access:https://www.mdpi.com/2072-4292/12/11/1757

Internet

https://www.mdpi.com/2072-4292/12/11/1757

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