Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment
Anomaly detection is critical for enhancing operational efficiency, safety, and maintenance in industrial applications, particularly in the era of Industry 4.0 and IoT. While traditional anomaly detection approaches face limitations such as scalability issues, high false alarm rates, and reliance on...
Saved in:
| Main Authors: | Praveen Vijai, Bagavathi Sivakumar P |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003627 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Transformer–VAE Approach for Detecting Ship Trajectory Anomalies in Cross-Sea Bridge Areas
by: Jiawei Hou, et al.
Published: (2025-04-01) -
Multivariate Time Series Anomaly Detection Using Working Memory Connections in Bi-Directional Long Short-Term Memory Autoencoder Network
by: Xianghua Ding, et al.
Published: (2025-03-01) -
Hybrid-CID: Securing IoT with Mongoose Optimization
by: S. Merlin Sheeba, et al.
Published: (2025-03-01) -
Software Defect Prediction Based on Effective Fusion of Multiple Features
by: Chaozheng Zhang, et al.
Published: (2025-01-01) -
Detection and identification of non-technical loss based on electricity consumption curve and deep learning
by: WANG Yunjing, et al.
Published: (2025-06-01)