Novelty Detection Review State of Art and Discussion of New Innovations in The Main Application Domains

Novelty detection is the identification of new or unknown data or signals that a machine learning system is not aware of during training. It is one of the fundamental requirements of a good classification or identification system since sometimes the test data contains information about objects that were not known at the time of training the model. This survey aims to provide an updated and structured overview of recent studies and approaches of novelty detection that have appeared in the machine learning and deep learning after the last review of Novelty detection in 2014. We surveyed on various techniques and applications of novelty detection in the main application domains.