Pseudo-Labeling and Time-Series Data Analysis Model for Device Status Diagnostics in Smart Agriculture

Pseudo-Labeling and Time-Series Data Analysis Model for Device Status Diagnostics in Smart Agriculture

This study proposes an automated data-labeling model that combines a pseudo-labeling algorithm with waveform segmentation based on Long Short-Term Memory (LSTM) to effectively label time-series data in smart agriculture. This model aims to address the inefficiency of manual labeling for large-scale...

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Bibliographic Details
Main Authors: Minwoo Jung, Dae-Young Kim
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
smart agriculture
pseudo-labeling
time-series data
machine learning automation
IoT device status monitoring
Online Access:https://www.mdpi.com/2076-3417/14/22/10371

Internet

https://www.mdpi.com/2076-3417/14/22/10371

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