A review of novelty detection

Cited by (1,003)

Items 801–900 of 1,003

  1. Which Outlier Detector Should I use?
    Kai Ming Ting, Sunil Aryal, Takashi Washio · 2018 · Proceedings
  2. Towards Autonomous Knowledge Creation from Big Data in Smart Cities
    Sławomir Nowaczyk, Thorsteinn S. Rognvaldsson, Yuantao Fan, Ece Calikus · 2020 · Springer eBooks
  3. Graph iForest: Isolation of anomalous and outlier graphs
    Daniele Zambon, Lorenzo Livi, Cesare Alippi · 2022 · International Joint Conference on Neural Networks (IJCNN)
  4. A-contrario detection and tracking from optical telescope data
    Benjamin G. Feuge-Miller, Moriba Kemessia Jah, Apoorva T. Karra, Shiva Iyer, D. Kucharski · 2023 · Acta Astronautica
  5. Research on Anomaly Detection in Time Series: Exploring United States Exports and Imports Using Long Short-Term Memory
    Sakshi AGGARWAL · 2023 · Journal of Research Innovation and Technologies
  6. Integrative conformal p-values for out-of-distribution testing with labelled outliers
    Ziyi Liang, Matteo Sesia, Wenguang Sun · 2024 · Journal of the Royal Statistical Society Series B (Statistical Methodology)
  7. A new strategy for data-driven damage diagnosis of shear structures adapted to ambient vibration
    Xuan Zhang, Luyu Li · 2024 · Measurement
  8. Anomaly‐based Alzheimer's disease detection using entropy‐based probability Positron Emission Tomography images
    Husnu Baris Baydargil, Jang‐Sik Park, İbrahim Furkan İnce · 2024 · ETRI Journal
  9. A one-class approach to cardiotocogram assessment
    Dimitris Gavrilis, George Nikolakopoulos, George Georgoulas · 2015 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  10. Semi-supervised Learning Using Incremental Support Vector Machine and Extreme Value Theory in Gesture Data
    Husam Al-Behadili, A. Grumpe, Lubaba Migdadi, Christian Wöhler · 2016 · UKSim International Conference on Computer Modelling and Simulation (UKSim)
  11. Evolutionary Optimization of an Affine Model for Vulnerability Characterization in Smart Grids
    Enrico De Santis, Maurizio Paschero, Antonello Rizzi, Fabio Massimo Frattale Mascioli · 2018 · International Joint Conference on Neural Networks (IJCNN)
  12. Data Analytics for Performance Evaluation Under Uncertainties Applied to an Industrial Refrigeration Plant
    Josep Cirera, Jesus A. Carino, Daniel Zurita, J. A. Ortega · 2019 · IEEE Access
  13. Usage Identification of Anomaly Detection in an Industrial Context
    Firas Zoghlami, Philip Kurrek, Mark Jocas, Giovanni Luca Masala, Vahid Salehi · 2019 · Proceedings of the ... International Conference on Engineering Design
  14. Automated active fault detection in fouled dissolved oxygen sensors
    Oscar Samuelsson, Jesús Zambrano, Anders Björk, Bengt Carlsson · 2019 · Water Research
  15. Anomaly Detection for Visual Quality Control of 3D-Printed Products
    Loek Tonnaer, Jiapeng Li, Vladimir Osin, Mike Holenderski, Vlado Menkovski · 2019 · International Joint Conference on Neural Networks (IJCNN)
  16. Introduction to Extreme Seeking Entropy
    Jan Vrba, Jan Mareš · 2020 · Entropy
  17. Flagging Implausible Inspection Reports of Distribution Transformers via Anomaly Detection
    Bin Xiang, Zhixiong Liu, Kunyi Zhang · 2020 · IEEE Access
  18. A Robotics Inspection System for Detecting Defects on Semi-specular Painted Automotive Surfaces
    Sohail Akhtar, Adarsh Tandiya, Medhat A. Moussa, Cole Tarry · 2020 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
  19. CNN‐based novelty detection for terrestrial and extra‐terrestrial autonomous exploration
    Loukas Bampis, Antonios C. Gasteratos, Evangelos Boukas · 2021 · IET Cyber-Systems and Robotics
  20. Triangle-based outlier detection
    Jorge Navarro, Isaac Martín de Diego, Rubén R. Fernández, Javier M. Moguerza · 2022 · Pattern Recognition Letters
  21. SNDProb: A probabilistic approach for streaming novelty detection
    Ander Carreño, Iñaki Inza, Jose Antonio Lozano · 2022 · IEEE Transactions on Knowledge and Data Engineering
  22. Novelty detection for metabolic dynamics established on breast cancer tissue using 2D NMR TOCSY spectra
    Lubaba Migdadi, Ahmad Telfah, Roland Hergenröder, Christian Wöhler · 2022 · Computational and Structural Biotechnology Journal
  23. Machine Learning for Cyber Physical Systems
    2019 · Technologien für die intelligente Automation
  24. Machine Learning Techniques and Systems for Mask-Face Detection—Survey and a New OOD-Mask Approach
    Youwen Hu, Yicheng Xu, Huiping Zhuang, Zhenyu Weng, Zhiping Lin · 2022 · Applied Sciences
  25. A Hybrid Clustering Approach Based on Fuzzy Logic and Evolutionary Computation for Anomaly Detection
    Shakhnaz Akhmedova, Становов Владимир Вадимович, Yukihiro Kamiya · 2022 · Algorithms
  26. Fast and Efficient Image Novelty Detection Based on Mean-Shifts
    Matthias Hermann, Georg Umlauf, Bastian Goldlüecke, Matthias Franz · 2022 · Sensors
  27. An active inference approach to on-line agent monitoring in safety–critical systems
    Luis O. Ávila, Ernesto Carlos Martinez · 2015 · Advanced Engineering Informatics
  28. Application of SsVGMM to medical data - classification with novelty detection
    Fan Yang, Jaymar Soriano, Takatomi Kubo, Kazushi Ikeda · 2017 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  29. Probabilistic Data-Driven Method for Limb Movement Detection during Sleep
    Matteo Cesari, Julie Anja Engelhard Christensen, Poul Jennum, Helge B. D. Sørensen · 2018 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  30. Forecasting and Early Warning for Adversarial Targeting in Industrial Control Systems
    Masoud Abbaszadeh, Lalit K. Mestha, Weizhong Yan · 2018 · IEEE Conference on Decision and Control (CDC)
  31. Cognitive Identity Management: Synthetic Data, Risk and Trust
    Svetlana N. Yanushkevich, Adrian Stoica, Peter Shmerko, W.G.J. Howells, Keeley A. Crockett, Richard Guest · 2020 · International Joint Conference on Neural Networks (IJCNN)
  32. Efficient Kernel Cook's Distance for Remote Sensing Anomalous Change Detection
    José A. Padrón Hidalgo, Adrián Pérez-Suay, Fatih Nar, Valero Laparra, Gustau Camps‐Valls · 2020 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  33. Incorporating User Feedback Into One-Class Support Vector Machines for Anomaly Detection
    Julien Lesouple, Jean‐Yves Tourneret · 2020 · European Signal Processing Conference (EUSIPCO)
  34. Spectral-texture approach to hyperspectral image analysis for plant classification with SVMs
    Ali AlSuwaidi, Bruce Grieve, Hujun Yin · 2017 · IEEE International Conference on Imaging Systems and Techniques (IST)
  35. Towards Identifying and Managing Sources of Uncertainty in AI and Machine Learning Models - An Overview
    Michael Kläs · 2018 · arXiv (Cornell University)
  36. Out-of-Distribution Detection with Distance Guarantee in Deep Generative Models
    Yufeng Zhang, Wanwei Liu, Zhenbang Chen, Ji Wang, Zhiming Liu, Kenli Li, Hongmei Wei, Zuoning Chen · 2020 · arXiv (Cornell University)
  37. GenQ: Quantization in Low Data Regimes with Generative Synthetic Data
    Yuhang Li, Youngeun Kim, Donghyun Lee, Souvik Kundu, Priyadarshini Panda · 2024 · Lecture notes in computer science
  38. Enhanced anomaly traffic detection framework using BiGAN and contrastive learning
    Haoran Yu, Wenchuan Yang, Baojiang Cui, Runqi Sui, Xuedong Wu · 2024 · Cybersecurity
  39. Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion
    Yuelong Liang, Haorui Liu, Yayu Chen · 2024 · Applied Sciences
  40. A Conceptual Framework for Measuring Ecological Novelty
    Timothy L. Staples, Jessica L. Blois, Katie L. Cramer, Emer T. Cunningham, María Dornelas, Simon Graeme Haberle, Tina Heger, Wolfgang Kiessling, Anne E. Magurran, Aaron O’Dea et al. · 2025 · Global Ecology and Biogeography
  41. Data-Driven Semi-Supervised Machine Learning with Safety Indicators for Abnormal Driving Behavior Detection
    Yongqi Dong, Lanxin Zhang, Haneen Farah, Arkady Zgonnikov, Bart van Arem · 2025 · Transportation Research Record Journal of the Transportation Research Board
  42. Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code
    Stefano Dalla Palma, Majid Mohammadi, Dario Di Nucci, Damian A. Tamburri · 2020
  43. Heart Disease Prediction based on Physiological Parameters Using Ensemble Classifier and Parameter Optimization
    Agung Muliawan, A. Rizal, S. Hadiyoso · 2023 · Journal of Applied Engineering and Technological Science (JAETS)
  44. Unsupervised damage assessment under varying ambient temperature based on an adjusted artificial neural network and new multivariate covariance-based distances
    Ali Nikdel, Hashem Shariatmadar · 2024 · Structural Health Monitoring
  45. Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts
    Marco A. F. Pimentel, Alistair E. W. Johnson, Julie Lorraine Darbyshire, Lionel Tarassenko, David Andrew Clifton, Andrew Walden, Ian Rechner, Peter Watkinson, Duncan Young · 2024 · BMJ Open
  46. Using a surrogate model for the detection of defective PWR fuel rods
    Karine Chevalier-Jabet, L. Verma, Francois Kremer · 2024 · Annals of Nuclear Energy
  47. Double kernel and minimum variance embedded broad learning system based autoencoder for one-class classification
    Ningxia He, Junwei Duan, Jun Lyu · 2024 · Neurocomputing
  48. Using AI to Improve Risk Management: A Case Study of a Leading Telecommunications Provider
    Helena Richard, Peter Dornheim, Thorsten Weber · 2024 · IEEE Access
  49. Anomaly Detection in High-Dimensional Time Series Data with Scaled Bregman Divergence
    Yunge Wang, Lingling Zhang, Tong Si, Graham Bishop, Haijun Gong · 2025 · Algorithms
  50. Can Your Generative Model Detect Out-of-Distribution Covariate Shift?
    Christiaan G. A. Viviers, M. M. Amaan Valiuddin, Francisco Caetano, Lemar Abdi, Lena Filatova, Peter H. N. de With, Fons van der Sommen · 2025 · Lecture notes in computer science
  51. Hybrid framework for categorising sounds of Mysticete whales
    Stavros Ntalampiras · 2016 · IET Signal Processing
  52. Edge-Based RNN Anomaly Detection Platform in Machine Tools
    Chia‐Yu Lin, Chih-Ping Weng, Li‐Chun Wang, Hong-Han Shuai, Wen-Peng Tseng · 2019 · Smart Science
  53. Automated design process for hybrid regression modeling with a one-class SVM
    Moritz Böhland, Wolfgang Doneit, Lutz Gröll, Ralf Mikut, Markus Reischl · 2019 · at - Automatisierungstechnik
  54. Kernel dependence analysis and graph structure morphing for novelty detection with high-dimensional small size data set
    Reza Mohammadi-Ghazi, Roy E. Welsch, Oral Büyüköztürk · 2020 · Mechanical Systems and Signal Processing
  55. Combining Classifiers for Foreign Pattern Rejection
    Władysław Homenda, Agnieszka Jastrzębska, Witold Pedrycz, Fusheng Yu · 2020 · Journal of Artificial Intelligence and Soft Computing Research
  56. Enhancing the Prediction of Mach Number in Wind Tunnel With a Regression-Based Outlier Detection Framework
    Hongyan Zhao, Dong Yu, Yue Wang, Biao Wang · 2021 · IEEE Access
  57. A novel semi-supervised framework for call center agent malpractice detection via neural feature learning
    Leonardo O. Iheme, Şükrü Ozan · 2022 · Expert Systems with Applications
  58. Power Disturbance Monitoring through Techniques for Novelty Detection on Wind Power and Photovoltaic Generation
    Artvin-Darien Gonzalez-Abreu, Roque Alfredo Osornio-Rios, David Alejandro Elvira‐Ortiz, Arturo Yosimar Jaen-Cuéllar, Miguel Delgado-Prieto, Jose Alfonso Antonino Daviu · 2023 · Sensors
  59. Knowledge Conditioned Variational Learning for One-Class Facial Expression Recognition
    Junjie Zhu, B. Luo, Tianyu Yang, Zewen Wang, Xibin Zhao, Yue Gao · 2023 · IEEE Transactions on Image Processing
  60. CROP: Towards Distributional-Shift Robust Reinforcement Learning Using Compact Reshaped Observation Processing
    Philipp J. Altmann, Fabian Ritz, Leonard Feuchtinger, Jonas Nüßlein, Claudia Linnhoff–Popien, Thomy Phan · 2023 · International Joint Conference on Artificial Intelligence
  61. Bridge Damage Detection Using Ambient Loads by Bayesian Hypothesis Testing for a Parametric Subspace of an Autoregressive Model
    Yoshinao Goi, Chul‐Woo Kim · 2023 · Structural Control and Health Monitoring
  62. Operations-aware novelty detection framework for CNC machine tools: proposal and application
    Marco Macchi, Laura Cattaneo, Adalberto Polenghi, Danilo Bruno, Sofia Mosci, Fabio Ferriani, Roberto Caneva · 2023 · The International Journal of Advanced Manufacturing Technology
  63. Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome k-mers
    Haotian Ren, Yixue Li, Tao Huang · 2023 · Microorganisms
  64. Enhanced recurrent network training
    Amir H. Jafari, Martin Hagan · 2015 · International Joint Conference on Neural Networks (IJCNN)
  65. Unsupervised Detection of Unusual Behaviors from Smart Home Energy Data
    Welma Pereira, Alois Ferscha, Klemens Weigl · 2016 · Lecture notes in computer science
  66. Evaluation of Novelty Detection Methods for Condition Monitoring applied to an Electromechanical System
    Miguel Delgado-Prieto, Jesus A. Carino, Daniel Zurita, Marta Millan Gonzalvez, J. A. Ortega, René de Jesús Romero-Troncoso · 2017 · InTech eBooks
  67. Real-time EMG-based Human Machine Interface using dynamic hand gestures
    Sungtae Shin, Reza Tafreshi, Reza Langari · 2017 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
  68. Learning the Floor Type for Automated Detection of Dirt Spots for Robotic Floor Cleaning Using Gaussian Mixture Models
    Andreas Grünauer, Georg Halmetschlager-Funek, Johann Prankl, Markus Vincze · 2017 · Lecture notes in computer science
  69. Tracking Dynamics in Concurrent Digital Twins
    Michael Borth, Emile van Gerwen · 2018 · Springer eBooks
  70. One-class Random Maxout Probabilistic Network for Mobile Touchstroke Authentication
    Seokmin Choi, Inho Chang, Andrew Beng Jin Teoh · 2018 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
  71. Rumour As an Anomaly: Rumour Detection with One-Class Classification
    Amir Ebrahimi Fard, Majid Mohammadi, Scott W. Cunningham, Bartel Van de Walle · 2019 · IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC)
  72. Outlier Mining Methods Based on Graph Structure Analysis
    Pablo Amil, Nahuel Almeira, Cristina Masoller · 2019 · Frontiers in Physics
  73. Online anomaly search in time series: significant online discords
    P. Avogadro, Luca Palonca, M. Dominoni · 2020 · Knowledge and Information Systems
  74. Toward Detecting Infection Incidence in People With Type 1 Diabetes Using Self-Recorded Data (Part 1): A Novel Framework for a Personalized Digital Infectious Disease Detection System
    Ashenafi Zebene Woldaregay, Ilkka Kalervo Launonen, Eirik Årsand, David J. Albers, Anna Holubová, Gunnar Hartvigsen · 2020 · Journal of Medical Internet Research
  75. Modelling and Recognition of Protein Contact Networks by Multiple Kernel Learning and Dissimilarity Representations
    Alessio Martino, Enrico De Santis, Alessandro Giuliani, Antonello Rizzi · 2020 · Entropy
  76. Design of a Deep Post Gripping Perception Framework for Industrial Robots
    Firas Zoghlami, Philip Kurrek, Mark Jocas, Giovanni Luca Masala, Vahid Salehi · 2020 · Journal of Computing and Information Science in Engineering
  77. Task-Aware Novelty Detection for Visual-based Deep Learning in Autonomous Systems
    Valerie Chen, Man-Ki Yoon, Zhong Shao · 2020 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
  78. Detecting Execution Anomalies As an Oracle for Autonomy Software Robustness
    Deborah S. Katz, Casidhe Hutchison, Milda Zizyte, Claire Le Goues · 2020 · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings
  79. Novelty Detection of Beverage Bottle Images Based on Transfer Learning
    Supanat Jintawatsakoon, Werayuth Charoenruengkit · 2020
  80. Machine Learning based calibration time reduction for Gas Sensors in Temperature Cycled Operation
    Yannick Robin, Payman Goodarzi, Tobias Baur, Caroline Schultealbert, Andreas Schütze, Tizian Schneider · 2021 · IEEE International Instrumentation and Measurement Technology Conference
  81. Sequential Gaussian Process Regression for Simultaneous Pathology Detection and Shape Reconstruction
    Dana Rahbani, Andreas Morel-Forster, Dennis Madsen, Jonathan Aellen, Thomas R. Vetter · 2021 · Lecture notes in computer science
  82. Comparative Evaluation of Semi-Supervised Anomaly Detection Algorithms on High-Integrity Digital Systems
    Gianluca Martino, Arne Grünhagen, Julien Branlard, Annika Eichler, Görschwin Fey, H. Schlarb · 2021 · Euromicro Conference on Digital System Design (DSD)
  83. An Unsupervised Noisy Sample Detection Method for Deep Learning-Based Health Status Prediction
    Yan‐Hui Lin, Liang Chang · 2021 · IEEE Transactions on Instrumentation and Measurement
  84. An Anomaly Detection Model for ADS-B Systems Based on Improved GAN and LSTM Networks
    Xinying Guo, Chunhua Zhu, Jing Yang, Yan Xiao · 2021 · IEEE International Conference on Communication Technology (ICCT)
  85. Variational Autoencoder with Gaussian Random Field prior: Application to unsupervised animal detection in aerial images
    Hugo Gangloff, Minh‐Tan Pham, Luc Courtrai, Sébastien Lefèvre · 2024 · ISPRS Journal of Photogrammetry and Remote Sensing
  86. Novelty Detection based Condition Monitoring Scheme Applied to Electromechanical Systems
    Miguel Delgado-Prieto, Jesus A. Carino, Juan José Saucedo-Dorantes, Roque Alfredo Osornio-Rios, Luis Romeral, René de Jesús Romero-Troncoso · 2018 · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
  87. Anomaly Detection for Short Texts: Identifying Whether Your Chatbot Should Switch from Goal-Oriented Conversation to Chit-Chatting
    Amir Bakarov, Vasiliy Yadrintsev, Илья Владимирович Соченков · 2018 · Communications in computer and information science
  88. A Two-Step Framework for Novelty Detection in Activities of Daily Living
    Silvia Rossi, Luigi Bove, Sergio Di Martino, Giovanni Ercolano · 2018 · Lecture notes in computer science
  89. Security of Data Science and Data Science for Security
    Bernhard Tellenbach, Marc Rennhard, Remo Schweizer · 2019 · Springer eBooks
  90. Trajectory-based gait pattern shift detection for assistive robotics applications
    João Paulo, Paulo Peixoto, Paula Amorim · 2019 · Intelligent Service Robotics
  91. How to Detect Novelty in Textual Data Streams? A Comparative Study of Existing Methods
    Clément Christophe, Julien Velcin, Jairo Cugliari, Philippe Suignard, Manel Boumghar · 2020 · Lecture notes in computer science
  92. History-Based Anomaly Detector: An Adversarial Approach to Anomaly Detection
    Pierrick Chatillon, Coloma Ballester · 2020 · Advances in intelligent systems and computing
  93. Novel Feature Extraction Methods for Authentication via Mouse Dynamics with Semi-Supervised Learning
    Metehan Yıldırım, Emin Anarım · 2019 · Innovations in Intelligent Systems and Applications Conference (ASYU)
  94. Parameterless Semi-supervised Anomaly Detection in Univariate Time Series
    Oleg Iegorov, Sebastian Fischmeister · 2021 · Lecture notes in computer science
  95. A novelty detection approach to monitoring of epicyclic gearbox health
    Ziemowit Dworakowski, Kajetan Dziedziech, Adam Jabłoński · 2018 · Metrology and Measurement Systems
  96. Detecting anomalies in robot time series data using stochastic recurrent networks
    Maximilian Sölch · 2015 · KTH Publication Database DiVA (KTH Royal Institute of Technology)
  97. On Anomaly Interpretation via Shapley Values
    Naoya Takeishi, Yoshinobu Kawahara · 2020 · arXiv (Cornell University)
  98. A Unifying Framework for Formal Theories of Novelty:Framework, Examples and Discussion
    Terrance E. Boult, Przemyslaw A. Grabowicz, Derek S. Prijatelj, Roni Stern, Larry B. Holder, J. Alspector, Mohsen Jafarzadeh, Touqeer Ahmad, Akshay Raj Dhamija, Li, C. et al. · 2020 · arXiv (Cornell University)
  99. Are Bayesian neural networks intrinsically good at out-of-distribution detection?
    Henning, Christian, D'Angelo, Francesco, Benjamin F. Grewe · 2021 · Zurich Open Repository and Archive (University of Zurich)
  100. Uncertainty-based out-of-distribution detection requires suitable function space priors.
    Francesco D’Angelo, Christian Henning · 2021 · arXiv (Cornell University)