Representation Learning for Fine-Grained Change Detection

Representation Learning for Fine-Grained Change Detection

Fine-grained change detection in sensor data is very challenging for artificial intelligence though it is critically important in practice. It is the process of identifying differences in the state of an object or phenomenon where the differences are class-specific and are difficult to generalise. A...

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Bibliographic Details
Main Authors: Niall O’Mahony, Sean Campbell, Lenka Krpalkova, Anderson Carvalho, Joseph Walsh, Daniel Riordan
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sensors
Subjects:
change detection
representation learning
latent space visualisation
Online Access:https://www.mdpi.com/1424-8220/21/13/4486

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