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High-throughput molecular imaging via deep learning enabled Raman
  spectroscopy

High-throughput molecular imaging via deep learning enabled Raman spectroscopy

28 September 2020
C. Horgan
Magnus Jensen
A. Nagelkerke
J. St-Pierre
Tom Kamiel Magda Vercauteren
Molly M. Stevens
Mads S. Bergholt
ArXivPDFHTML

Papers citing "High-throughput molecular imaging via deep learning enabled Raman spectroscopy"

4 / 4 papers shown
Title
Hyperspectral unmixing for Raman spectroscopy via physics-constrained
  autoencoders
Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders
Dimitar Georgiev
Álvaro Fernández-Galiana
Simon Vilms Pedersen
Georgios Papadopoulos
Ruoxiao Xie
Molly M. Stevens
Mauricio Barahona
29
3
0
07 Mar 2024
When Bioprocess Engineering Meets Machine Learning: A Survey from the
  Perspective of Automated Bioprocess Development
When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development
Nghia Duong-Trung
Stefan Born
Jong Woo Kim
M. Schermeyer
Katharina Paulick
...
Thorben Werner
Randolf Scholz
Lars Schmidt-Thieme
Peter Neubauer
Ernesto Martinez
31
20
0
02 Sep 2022
spectrai: A deep learning framework for spectral data
spectrai: A deep learning framework for spectral data
C. Horgan
Mads S. Bergholt
VLM
18
4
0
17 Aug 2021
Adversarial training with cycle consistency for unsupervised
  super-resolution in endomicroscopy
Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy
D. Ravì
A. Szczotka
Stephen P. Pereira
Tom Kamiel Magda Vercauteren
SupR
MedIm
27
49
0
21 Jan 2019
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