On Anomalous Deformation Profile Detection Through Supervised and Unsupervised Machine Learning.
Stefan-Adrian TomaBogdan SebacherAdrian FocsaMihai-Lica PuraPublished in: IGARSS (2019)
Keyphrases
- machine learning
- supervised learning
- unsupervised learning
- anomaly detection
- supervised classification
- learning algorithm
- feature selection
- semi supervised
- supervised and unsupervised learning
- pattern recognition
- false positives
- detection algorithm
- detection rate
- unsupervised methods
- detection method
- supervised and semi supervised
- learning tasks
- machine learning methods
- false alarms
- machine learning algorithms
- discriminant projection
- knowledge acquisition
- semi supervised learning
- natural language processing
- decision trees
- weakly supervised
- detection accuracy
- pairwise
- computer vision
- detecting anomalous
- supervised methods
- active learning
- knowledge representation
- learning problems
- intrusion detection
- deep learning
- unsupervised feature selection
- computer science
- computational intelligence
- text classification
- artificial intelligence