A Cross-Modal Dynamic Attention Neural Architecture to Detect Anomalies in Data Streams from Smart Communication Environments

A Cross-Modal Dynamic Attention Neural Architecture to Detect Anomalies in Data Streams from Smart Communication Environments

Detecting anomalies in data streams from smart communication environments is a challenging problem that can benefit from novel learning techniques. The Attention Mechanism is a very promising architecture for addressing this problem. It allows the model to focus on specific parts of the input data w...

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Bibliographic Details
Main Authors: Konstantinos Demertzis, Konstantinos Rantos, Lykourgos Magafas, Lazaros Iliadis
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Applied Sciences
Subjects:
cross-modal learning tasks
dynamic attention mechanism
neural architecture
anomaly detection
data streams
smart communication environments
Online Access:https://www.mdpi.com/2076-3417/13/17/9648

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