ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2109.01403
  4. Cited By
Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral
  Correction and High-resolution RGB Reconstruction

Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction

3 September 2021
Peichao Li
Michael Ebner
P. Noonan
C. Horgan
Anisha Bahl
Sebastien Ourselin
J. Shapey
Tom Kamiel Magda Vercauteren
ArXivPDFHTML

Papers citing "Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction"

3 / 3 papers shown
Title
Hyperspectral Image Segmentation: A Preliminary Study on the Oral and
  Dental Spectral Image Database (ODSI-DB)
Hyperspectral Image Segmentation: A Preliminary Study on the Oral and Dental Spectral Image Database (ODSI-DB)
Luis C. García-Peraza-Herrera
C. Horgan
Sebastien Ourselin
Michael Ebner
Tom Kamiel Magda Vercauteren
39
33
0
14 Mar 2023
Spatial gradient consistency for unsupervised learning of hyperspectral
  demosaicking: Application to surgical imaging
Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: Application to surgical imaging
Peichao Li
Muhammad Asad
C. Horgan
O. MacCormac
J. Shapey
Tom Kamiel Magda Vercauteren
23
7
0
21 Feb 2023
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and
  Results
NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
Andreas Lugmayr
Martin Danelljan
Radu Timofte
Namhyuk Ahn
Dongwoon Bai
...
Tongtong Zhao
Yuanbo Zhou
Haijie Zhuo
Ziyao Zong
Xueyi Zou
SupR
94
170
0
05 May 2020
1