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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders

For many sensing applications, collecting a large experimental dataset could be a time-consuming and expensive task that can also hinder the implementation of Machine Learning models for analyzing sensor data. Therefore, this paper proposes the generation of synthetic signals through a Variational A...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo
Format: Artigo
Sprache:Inglês
Veröffentlicht: IOP Publishing 2025-01-01
Schriftenreihe:Machine Learning: Science and Technology
Schlagworte:
variational autoencoders
latent space search
data augmentation
synthetic data
generative models
capacitive sensors
Online-Zugang:https://doi.org/10.1088/2632-2153/adb009
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