Skip to content
RDL
Network
Ecosystem
Switch app
TR
About
FAQ
Sign in
Get started
Validating neural networks for spectroscopic classification on a universal synthetic dataset — Jan Schuetzke (2023) | RDL Network
Back
Cite
Save
Save for later
Share
Home
Publications
Validating neural networks for spectroscopic classification on a universal synthetic dataset
Shared by
Nathan J Szymanski
University of California, Berkeley
Validating neural networks for spectroscopic classification on a universal synthetic dataset
Article
2023
en
Authors
JS
Jan Schuetzke
Nathan J Szymanski
University of California, Berkeley
MR
Markus Reischl
Discussion
(0)
Sign in
to like and join the discussion.
No comments yet. Be the first to comment.
Related publications
Preprint
2022
A universal synthetic dataset for machine learning on spectroscopic data
Jan Schuetzke
,
Nathan J Szymanski
,
Markus Reischl
Article
2010
Traffic classification using probabilistic neural networks
Runyuan Sun
,
Bo Yang
,
Lizhi Peng
,
Zhenxiang Chen
,
Lei Zhang
,
Shan Jing
Article
2022
Worker’s physical fatigue classification using neural networks
Elena Escobar-Linero
,
Manuel Jesus Dominguez Morales
,
José Luis Sevillano
Article
2024
Convolutional Fuzzy Neural Networks With Random Weights for Image Classification
Yifan Wang
,
Hisao Ishibuchi
,
Witold Pedrycz
,
Jihua Zhu
,
Xiangyong Cao
,
Jun Wang
Article
2020
Low-Power Embedded System for Gait Classification Using Neural Networks
Francisco Luna-Perejón
,
Manuel Jesus Dominguez Morales
,
Daniel Gutiérrez-Galán
,
A Balcells
Discussion(0)
No comments yet. Be the first to comment.