"Control Charts and Machine Learning for Anomaly Detection in Manufacturing"

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Book	Author(s)	Year	Publisher
Control Charts and Machine Learning for Anomaly Detection in Manufacturing	Kim Phuc Tran	1st ed. 2022	Springer International Publishing
Network Anomaly Detection: A Machine Learning Perspective	Dhruba Kumar Bhattacharyya; Jugal Kumar Kalita	2013	Routledge
Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video	Olga Isupova	1st ed. 2018	Springer International Publishing
Traffic Anomaly Detection	Cuadra-Sánchez Antonio and Javier Aracil-Rico	2016	Elsevier
Anomaly Detection Principles and Algorithms	Kishan G. Mehrotra; Chilukuri K. Mohan; HuaMing Huang	1st ed. 2017	Springer International Publishing
Anomaly Detection: Techniques and Applications	Saira Banu, Shriram Raghunathan, Dinesh Mavaluru, A. Syed Mustafa	2021	Nova Science
Moving Objects Detection Using Machine Learning	Navneet Ghedia; Chandresh Vithalani; Ashish M. Kothari; Rohit M. Thanki	1st ed. 2022	Springer International Publishing
Intrusion detection: a machine learning approach	Zhenwei Yu	2011	Imperial College Press;Distributed by World Scientific
SCADA Security: Machine Learning Concepts for Intrusion Detection and Prevention	Abdulmohsen Almalawi; Zahir Tari; Adil Fahad; Xun Yi	2021	Wiley Data and Cybersecurity
Beginning Anomaly Detection Using Python-Based Deep Learning: With Keras and PyTorch	Sridhar Alla; Suman Kalyan Adari	1st ed.	Apress
Optimization and Machine Learning - Optimizationfor Machine Learning and Machine Learning for Optimization	Rachid Chelouah; Patrick Siarry	2022	John Wiley & Sons
Machine Learning for Solar Array Monitoring, Optimization, and Control	Sunil Rao; Sameeksha Katoch; Vivek Narayanaswamy; Gowtham Muniraju; Cihan Tepedelenlioglu; Andreas Spanias		Springer International Publishing
Anomaly-Detection and Health-Analysis Techniques for Core Router Systems	Shi Jin; Zhaobo Zhang; Krishnendu Chakrabarty; Xinli Gu	1st ed. 2020	Springer International Publishing
A Machine-Learning Approach to Phishing Detection and Defense	I.S. Amiri; O.A. Akanbi and E. Fazeldehkordi	2015	Syngress
empirical comparison of monitoring algorithms for access anomaly detection	Anne Dinning	1989	Courant Institute of Mathematical Sciences, New York University
An evaluation of monitoring algorithms for access anomaly detection	Anne Dinning	1989	Courant Institute of Mathematical Sciences, New York University
An evaluation of monitoring algorithms for access anomaly detection	Anne Dinning	1989	Courant Institute of Mathematical Sciences, New York University
Control Charts	J. Murdoch (auth.)	1979	Macmillan Education UK
Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots	Bojan Jakimovski	2011	Springer Berlin Heidelberg
Machine Learning Control by Symbolic Regression	Askhat Diveev; Elizaveta Shmalko	1st ed. 2021	Springer International Publishing
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Introduction to Control Charts and Machine Learning for Anomaly Detection in Manufacturing	Kim Phuc Tran	Control Charts and Machine Learning for Anomaly Detection in Manufacturing	Kim Phuc Tran	1st ed. 2022	Springer International Publishing
Machine Learning for Anomaly Detection	Sumeet Dua; Xian Du	Data Mining and Machine Learning in Cybersecurity	Sumeet Dua; Xian Du	2011	Routledge
Machine Learning: Anomaly Detection		Prognostics and Health Management of Electronics: Fundamentals, Machine Learning, and the Internet of Things	Michael G. Pecht; Myeongsu Kang	2019	Wiley-IEEE Press
4 Machine Learning for Anomaly Detection		Security in Autonomous Driving	Obaid Ur-Rehman; Natasa Zivic	2020	De Gruyter Oldenbourg
9 - Machine learning for intrusion and anomaly detection		Network Security: A Decision and Game-Theoretic Approach	Tansu Alpcan; Tamer Başar	2010-10	Cambridge University Press
Combining Machine Learning and Semantics for Anomaly Detection	Badre Belabbess; Musab Bairat; Jeremy Lhez; Olivier Curé	Knowledge Engineering and Knowledge Management: 21st International Conference, EKAW 2018, Nancy, France, November 12-16, 2018, Proceedings	Catherine Faron Zucker; Chiara Ghidini; Amedeo Napoli; Yannick Toussaint	1st ed. 2018	Springer International Publishing
Anomaly Detection in IoT Using Machine Learning	Saadat Hasan Khan; Aritro Roy Arko; Amitabha Chakrabarty	Artificial Intelligence for Cloud and Edge Computing	Sanjay Misra; Amit Kumar Tyagi; Vincenzo Piuri; Lalit Garg	1st ed. 2022	Springer International Publishing
Applications of Machine Learning in Anomaly Detection	Gadilli Sai Nikhil; Arun Sekar Rajasekaran; Madupathi Parimala; S. Velliangiri	Computational Intelligence in Machine Learning: Select Proceedings of ICCIML 2021	Amit Kumar; Jacek M. Zurada; Vinit Kumar Gunjan; Raman Balasubramanian	1st ed. 2022	Springer Nature Singapore
Machine Learning-Based Anomaly Prediction for Smart Manufacturing	Giovanni Diraco; Pietro Siciliano; Alessandro Leone	Sensors and Microsystems: Proceedings of AISEM 2021 – In Memory of Arnaldo D’Amico	Girolamo Di Francia; Corrado Di Natale	1st ed. 2023	Springer International Publishing
Anomaly detection using machine learning algorithms	Y. Pant; A. Cheema; B. Negi	Smart Computing: Proceedings of the 1st International Conference on Smart Machine Intelligence and Real-Time Computing (SmartCom 2020), 26-27 June 2020, Pauri, Garhwal, Uttarakhand, India	Mohammad Ayoub Khan; Sanjay Gairola; Bhola Jha; Pushkar Praveen	2021	Routledge
Chapter 11: Machine Learning Anomaly Detection		Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization	Stefanie Molin	2021	Packt Publishing
Machine Learning-Driven Algorithms for Network Anomaly Detection	Md. Sirajul Islam; Mohammad Abdur Rouf; A. H. M. Shahariar Parvez; Prajoy Podder	Inventive Computation and Information Technologies: Proceedings of ICICIT 2021	S. Smys; Valentina Emilia Balas; Ram Palanisamy	1st ed. 2022	Springer Nature Singapore
Anomaly Detection in Drones with Machine Learning Algorithms	Soumya Shaw; Kartik Joshi; Akhil Pathak; Abitha K. Thyagarajan; G. Vidya; Rahul Hemal Shah et al.	Futuristic Communication and Network Technologies: Select Proceedings of VICFCNT 2020	A. Sivasubramanian; Prasad N. Shastry; Pua Chang Hong	1st ed. 2022	Springer Nature Singapore
Anomaly Detection in Cellular IoT with Machine Learning	Bernardo Santos; Imran Qayyrm Khan; Bruno Dzogovic; Boning Feng; Van Thuan Do; Niels Jacot et al.	Smart Objects and Technologies for Social Good: 7th EAI International Conference, GOODTECHS 2021, Virtual Event, September 15–17, 2021, Proceedings	Ivan Miguel Pires; Susanna Spinsante; Eftim Zdravevski; Petre Lameski	1st ed. 2021	Springer International Publishing
Anomaly Detection in HTTP Requests Using Machine Learning	Ayush Gupta; Avani Modak	Machine Learning and Information Processing: Proceedings of ICMLIP 2020	Debabala Swain; Prasant Kumar Pattnaik; Tushar Athawale	1st ed. 2021	Springer Nature Singapore
Learning approaches for anomaly detection		Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines	Kirill Kolodiazhnyi	2020	Packt Publishing
Semi-unsupervised Machine Learning for Anomaly Detection in HTTP Traffic	Rafał Kozik; Michał Choraś; Rafał Renk; Witold Hołubowicz	Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015	Robert Burduk; Konrad Jackowski; Marek Kurzynski; Michal Wozniak; Andrzej Zolnierek	1st ed. 2016	Springer International Publishing
Anomaly Detection Using Unsupervised Machine Learning Algorithms	Pavitra Kadiyala; K. V. Shanmukhasai; Sai Shashank Budem; Praveen Kumar Reddy Maddikunta	Deep Learning for Security and Privacy Preservation in IoT	Aaisha Makkar; Neeraj Kumar	1st ed. 2021	Springer Nature Singapore
Machine Learning Approach for IP-Flow Record Anomaly Detection	Cynthia Wagner; Jérôme François; Radu State; Thomas Engel	NETWORKING 2011: 10th International IFIP TC 6 Networking Conference, Valencia, Spain, May 9-13, 2011, Proceedings, Part I	Jordi Domingo-Pascual; Pietro Manzoni; Sergio Palazzo; Ana Pont; Caterina Scoglio	2011	Springer Berlin Heidelberg
3 Machine Learning-based Anomaly Detection for Cybersecurity Applications		Machine Learning and Probabilistic Graphical Models for Decision Support Systems	Kim Phuc Tran	2022	CRC Press
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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