A review of novelty detection

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A neural data structure for novelty detection

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Road Anomaly Detection Through Deep Learning Approaches

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A Survey on Learning to Reject

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A Comprehensive Survey on Rare Event Prediction

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Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers' compensation fraud

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Where's Wally Now? Deep Generative and Discriminative Embeddings for Novelty Detection

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Aircraft Fleet Health Monitoring with Anomaly Detection Techniques

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A Survey on Open Set Recognition

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A new Growing Neural Gas for clustering data streams

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Feature-Ensemble-Based Novelty Detection for Analyzing Plant Hyperspectral Datasets

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Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results

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Localized Multiple Kernel learning for Anomaly Detection: One-class Classification

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A bibliometric analysis of cyber security and cyber forensics research

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Machine learning application in modelling marine and coastal phenomena: a critical review

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On the Evaluation of Outlier Detection and One-Class Classification Methods

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Active learning for classifying data streams with unknown number of classes

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Multimodal anomaly detection for assistive robots

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q-Space Novelty Detection with Variational Autoencoders

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A discrepancy analysis methodology for rolling element bearing diagnostics under variable speed conditions

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Outside the Box: Abstraction-Based Monitoring of Neural Networks

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ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids

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Semi-Supervised Time Series Anomaly Detection Based on Statistics and Deep Learning

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Detecting Outliers with Foreign Patch Interpolation

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Attribute Restoration Framework for Anomaly DetectionPreprint

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A collective AI via lifelong learning and sharing at the edge

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New Trends in the Use of Artificial Intelligence for the Industry 4.0

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CAM-guided Multi-Path Decoding U-Net with Triplet Feature Regularization for Defect Detection and Segmentation

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Taxonomy of Anomaly Detection Techniques in Crowd Scenes

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On the construction of extreme learning machine for online and offline one-class classification—An expanded toolbox

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An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving

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Topological obstructions to autoencoding

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Variational Inference for On-line Anomaly Detection in High-Dimensional Time SeriesPreprint

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Using Machine Learning Safely in Automotive Software: An Assessment and Adaption of Software Process Requirements in ISO 26262Preprint

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Target specific mining of COVID-19 scholarly articles using one-class approach

Sonbhadra, S. K., Agarwal, S., & Nagabhushan, P. N. (2020) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2020.110155 · Cited by 47

A novelty detection approach to diagnosing hull and propeller fouling

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Detecting Gas Turbine Combustor Anomalies Using Semi-supervised Anomaly Detection with Deep Representation Learning

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A Modified DBSCAN Algorithm for Anomaly Detection in Time-series Data with Seasonality

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Filter Feature Selection for One-Class Classification

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Anomaly Detection and Classification in Multispectral Time Series Based on Hidden Markov Models

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Why does my model fail?

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Rethinking Assumptions in Deep Anomaly DetectionPreprint

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Large margin distribution multi-class supervised novelty detection

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A general framework to govern machine learning oriented materials data quality

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Novelty Detection with GANPreprint

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A comprehensive survey on the applications of machine learning techniques on maritime surveillance to detect abnormal maritime vessel behaviors

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Anomaly diagnosis of connected autonomous vehicles: A survey

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Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation

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GAN-Based Anomaly Detection In Imbalance Problems

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Data stream classification with novel class detection: a review, comparison and challenges

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Spatial verification using wavelet transforms: a review

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Graph Embedded One-Class Classifiers for media data classification

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A flexible machine vision system for small part inspection based on a hybrid SVM/ANN approach

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Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions

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Reducing false alarms in guided waves structural health monitoring of pipelines: Review synthesis and debate

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Why is the Mahalanobis Distance Effective for Anomaly Detection?Preprint

Kamoi, R., & Kobayashi, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.00402 · Cited by 91

Partially online damage detection using long-term modal data under severe environmental effects by unsupervised feature selection and local metric learning

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Detecting outliers and learning complex structures with large spectroscopic surveys – a case study with APOGEE stars

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An Unsupervised Data-Driven Anomaly Detection Approach for Adverse Health Conditions in People Living With Dementia: Cohort Study

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Structural Health Monitoring: from Structures to Systems-of-Systems ★ ★The support of the UK Engineering and Physical Sciences Research Council (EPSRC) through grant reference numbers EP/J016942/1 and EP/K003836/2, and that of the EU Framework 7 Programme for the ITN project SYSWIND, is gratefully acknowledged.

Keith Worden, B., Cross, E. J., Dervilis, N., Papatheou, E., & Antoniadou, I. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.09.497 · Cited by 41

Some Recent Developments in SHM Based on Nonstationary Time Series Analysis

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Novelty detection in images by sparse representations

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Clarifying Data Analytics Concepts for Industrial Engineering

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Supervised Machine-Learning Enables Segmentation and Evaluation of Heterogeneous Post-treatment Changes in Multi-Parametric MRI of Soft-Tissue Sarcoma

Blackledge, M., Winfield, J. M., Miah, A. B., Strauß, D., Thway, K., Morgan, V. A., Collins, D. J., Koh, D., Leach, M. O., & Messiou, C. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.00941 · Cited by 41

Deep Convolutional Clustering-Based Time Series Anomaly Detection

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A neurocomputational model of creative processes

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Data-Driven Fault Detection and Diagnosis: Challenges and Opportunities in Real-World Scenarios

Calabrese, F., Regattieri, A., Bortolini, M., & Galizia, F. G. (2022) · Applied Sciences · doi:10.3390/app12189212 · Cited by 40

Data Anomaly Detection for Structural Health Monitoring Based on a Convolutional Neural Network

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Anomaly-Based Intrusion Detection for IoMT Networks: Design, Implementation, Dataset Generation, and ML Algorithms Evaluation

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Class imbalance in unsupervised change detection – A diagnostic analysis from urban remote sensing

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Autonomously triggered model updates for self-learning thermal error compensation

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A three-way clustering approach for novelty detection

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Machine learning methods for vehicle predictive maintenance using off-board and on-board data

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Toward the Integration of Cyber and Physical Security Monitoring Systems for Critical Infrastructures

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Multi-stage temperature compensation method for Lamb wave measurements

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Systematic sensor placement for structural anomaly detection in the absence of damaged states

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One-Class Classification Based on Extreme Learning and Geometric Class Information

Iosifidis, A., Mygdalis, V., Tefas, A., & Pitas, I. (2016) · Neural Processing Letters · doi:10.1007/s11063-016-9541-y · Cited by 38

One-class extreme learning machines for gas turbine combustor anomaly detection

Yan, W. (2016) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2016.7727567 · Cited by 38

Combining univariate approaches for ensemble change detection in multivariate data

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A Novel and Efficient CVAE-GAN-Based Approach With Informative Manifold for Semi-Supervised Anomaly Detection

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Beyond ImageNet: Deep Learning in Industrial Practice

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Anomaly Detection in Trajectory Data with Normalizing Flows

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Topological obstructions to autoencoding

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Two-step residual-error based approach for anomaly detection in engineering systems using variational autoencoders

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MUD enabled deep learning framework for anomaly detection in IoT integrated smart building

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Anomaly Detection Methods for Industrial Applications: A Comparative Study

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Robot perception of static and dynamic objects with an autonomous floor scrubber

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Novelty detection in continuously changing environments

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Novelty detection of cable-stayed bridges based on cable force correlation exploration using spatiotemporal graph convolutional networks

Li, S., Niu, J., & Li, Z. (2021) · Structural Health Monitoring · doi:10.1177/1475921720988666 · Cited by 37

User Authentication via Electrical Muscle Stimulation

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Application of an Anomaly Detection Model to Screen for Ocular Diseases Using Color Retinal Fundus Images: Design and Evaluation Study

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StRegA: Unsupervised Anomaly Detection in Brain MRIs using Compact Context-encoding Variational Autoencoder

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