Semi-Supervised Learned Autoencoder for Classification of Events in Distributed Fibre Acoustic Sensors
The global market for infrastructure security systems based on distributed acoustic sensors is rapidly expanding, driven by the need for timely detection and prevention of potential threats. However, deploying these systems is challenging due to the high costs associated with dataset creation. Addit...
Saved in:
Main Authors: | Artem Kozmin, Oleg Kalashev, Alexey Chernenko, Alexey Redyuk |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-06-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/25/12/3730 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Separated and Independent Contrastive Semi-Supervised Learning for Imbalanced Datasets
by: Dongyoung Kim, et al.
Published: (2025-01-01) -
An in-depth exploration of supervised and semi-supervised learning on face recognition
by: Purnawansyah, et al.
Published: (2025-06-01) -
Leveraging Prior Knowledge in Semi-Supervised Learning for Precise Target Recognition
by: Guohao Xie, et al.
Published: (2025-07-01) -
UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification
by: Zeyu Ren, et al.
Published: (2024-01-01) -
Leveraging pre-trained models within a semi-supervised and explainable AI RealTime framework: A pioneering paradigm for betel leaf disease detection
by: Md Tahsin, et al.
Published: (2025-08-01)