The Concept of Using LSTM to Detect Moisture in Brick Walls by Means of Electrical Impedance Tomography
This paper refers to an original concept of tomographic measurement of brick wall humidity using an algorithm based on long short-term memory (LSTM) neural networks. The measurement vector was treated as a data sequence with a single time step in the presented study. This approach enabled the use of...
Enregistré dans:
| Auteurs principaux: | Grzegorz Kłosowski, Anna Hoła, Tomasz Rymarczyk, Łukasz Skowron, Tomasz Wołowiec, Marcin Kowalski |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/ead541ecd1414d3bb57bd0db98969f67 |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Comparison of Machine Learning Methods for Image Reconstruction Using the LSTM Classifier in Industrial Electrical Tomography
par: Grzegorz Kłosowski, et autres
Publié: (2021) -
Research on LSTM+Attention Model of Infant Cry Classification
par: Tianye Jian, et autres
Publié: (2021) -
Proyección del precio de criptomonedas basado en Tweets empleando LSTM
par: Regal,Andrés, et autres
Publié: (2019) -
Short-term prediction of wind power density using convolutional LSTM network
par: Gupta Deepak, et autres
Publié: (2021) -
An experimental and numerical study of moisture transport and moisture-induced strain in fast-grown Sitka spruce
par: O'Ceallaigh,Conan, et autres
Publié: (2019)