One-Class Classification in Images and Videos Using a Convolutional Autoencoder With Compact Embedding

One-Class Classification in Images and Videos Using a Convolutional Autoencoder With Compact Embedding

In One-Class Classification (OCC) problems, the classifier is trained with samples of a class considered normal, such that exceptional patterns can be identified as anomalies. Indeed, for real-world problems, the representation of the normal class in the feature space is an important issue, consider...

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Bibliographic Details
Main Authors: Manasses Ribeiro, Matheus Gutoski, Andre E. Lazzaretti, Heitor S. Lopes
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Anomaly detection
compact embedding
convolutional autoencoder
deep learning
feature extraction
one-class classification
Online Access:https://ieeexplore.ieee.org/document/9087874/

Internet

https://ieeexplore.ieee.org/document/9087874/

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