A Deep Convolutional Autoencoder-Based Approach for Anomaly Detection With Industrial, Non-Images, 2-Dimensional Data: A Semiconductor Manufacturing Case Study.
Marco MaggipintoAlessandro BeghiGian Antonio SustoPublished in: IEEE Trans Autom. Sci. Eng. (2022)
Keyphrases
- anomaly detection
- semiconductor manufacturing
- dimensional data
- intrusion detection
- image features
- image data
- anomalous behavior
- detecting anomalies
- image retrieval
- input image
- network traffic
- image classification
- network intrusion detection
- multi dimensional
- intrusion detection system
- data sets
- quad trees
- unsupervised learning
- deep learning
- pairwise
- object recognition
- network anomaly detection
- negative selection algorithm
- input data
- high dimensional
- one class support vector machines
- machine learning