A Comparison of Supervised and Unsupervised Deep Learning Methods for Anomaly Detection in Images.
Vincent WilmetSauraj VermaTabea RedlHåkon SandakerZhenning LiPublished in: CoRR (2021)
Keyphrases
- anomaly detection
- unsupervised learning
- deep learning
- intrusion detection
- test images
- machine learning
- image features
- network traffic
- supervised learning
- input image
- intrusion detection system
- network intrusion detection
- restricted boltzmann machine
- feature selection
- unsupervised anomaly detection
- one class support vector machines
- unsupervised feature learning
- semi supervised
- named entities
- segmentation method
- object recognition
- bayesian networks
- training data
- similarity measure
- face recognition
- data mining
- data sets