"Unsupervised deep learning-based process monitoring methods"

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Book	Author(s)	Year	Publisher
Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods	Chris Aldrich; Lidia Auret	2013	Springer London
Fusion Methods for Unsupervised Learning Ensembles	Bruno Baruque	2011	Springer Berlin Heidelberg
Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches	Amanda Hering; Fouzi Harrou; Muddu Madakyaru; Ying Sun andabdelkader Dairi	2020	Elsevier
Unsupervised Learning Algorithms	M. Emre Celebi, Kemal Aydin (eds.)	2016	Springer International Publishing
Unsupervised Learning Algorithms	M. Emre Celebi; Kemal Aydin	1st ed. 2016	Springer International Publishing
Deep Learning-Based Face Analytics	Nalini K Ratha; Vishal M. Patel; Rama Chellappa	1st ed. 2021	Springer International Publishing
Deep Learning: Methods and Applications	Li Deng, Dong Yu	2014	Now Publishers
Multivariate Statistical Process Control: Process Monitoring Methods and Applications	Zhiqiang Ge; Zhihuan Song	2013	Springer London
Deep Learning Based Speech Quality Prediction	Gabriel Mittag	1st ed. 2022	Springer International Publishing
Unsupervised Learning: A Dynamic Approach	Matthew Kyan; Paisarn Muneesawang; Kambiz Jarrah; Ling Guan	2014	Wiley-IEEE Press
Natural Computing for Unsupervised Learning	Xiangtao Li; Ka-Chun Wong	1st ed. 2019	Springer International Publishing
Methods of Model Based Process Control	R. Berber	1995	Springer Netherlands
Deep Learning-Based Approaches for Sentiment Analysis	Basant Agarwal; Richi Nayak; Namita Mittal; Srikanta Patnaik	1st ed. 2020	Springer Nature Singapore
Practical Deep Learning: A Python-Based Introduction	Ron Kneusel	2021	No Starch Press
Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks	Marius Leordeanu	1st ed. 2020	Springer International Publishing
Machine Learning Foundations: Supervised, Unsupervised, and Advanced Learning	Taeho Jo	1st ed. 2021	Springer International Publishing
Face Image Analysis by Unsupervised Learning	Marian Stewart Bartlett	2001	Springer US
Unsupervised Learning: Foundations of Neural Computation	Geoffrey Hinton; Terrence J. Sejnowski	1999	MIT Press,
Unsupervised learning: foundations of neural computation /	Hinton, Geoffrey E.; Sejnowski, Terrence J.	1999.	MIT Press,
Machine Learning Paradigms: Advances in Deep Learning-based Technological Applications	George A. Tsihrintzis; Lakhmi C. Jain	1st ed. 2020	Springer International Publishing
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Unsupervised deep learning-based process monitoring methods	Fouzi Harrou; Ying Sun; Amanda S. Hering; Muddu Madakyaru; Abdelkader Dairi	Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches	Amanda Hering; Fouzi Harrou; Muddu Madakyaru; Ying Sun andabdelkader Dairi	2020	Elsevier
Unsupervised recurrent deep learning scheme for process monitoring	Fouzi Harrou; Ying Sun; Amanda S. Hering; Muddu Madakyaru; Abdelkader Dairi	Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches	Amanda Hering; Fouzi Harrou; Muddu Madakyaru; Ying Sun andabdelkader Dairi	2020	Elsevier
Unsupervised deep learning	Juha Karhunen; Tapani Raiko; KyungHyun Cho	Advances in Independent Component Analysis and Learning Machines	Ella Bingham; S. Kaski; Jorma Laaksonen and Jouko Lampinen	2015	Academic Press
Unsupervised Deep Learning		Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data	Ankur A. Patel	2019	O'Reilly Media
Unsupervised Deep Learning	Akinori Tanaka; Akio Tomiya; Koji Hashimoto	Deep Learning and Physics	Akinori Tanaka; Akio Tomiya; Koji Hashimoto	1st ed. 2021	Springer Nature Singapore
Unsupervised Learning: Deep Learning	Andreas François Vermeulen	Industrial Machine Learning: Using Artificial Intelligence as a Transformational Disruptor	Andreas François Vermeulen	1st ed.	Apress
Unsupervised Learning Methods		Encyclopedia of Systems Biology	Werner Dubitzky; Olaf Wolkenhauer; Hiroki Yokota; Kwang-Hyun Cho	2013	Springer New York
Unsupervised Learning Methods	George Fernandez	Statistical Data Mining Using SAS Applications	George Fernandez	2011	Routledge
Unsupervised Learning Methods	Ashwin Pajankar; Aditya Joshi	Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch	Ashwin Pajankar; Aditya Joshi	1st ed.	Apress
Unsupervised Learning Methods		Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale (Addison-Wesley Data & Analytics)	Ofer Mendelevitch, Casey Stella, Douglas Eadline	2017	Addison-Wesley
Unsupervised Learning Methods		Principles of clinical cancer research	Loren K. Mell, MD, Phuoc T. Tran, MD, PhD, James B. Yu, MD, MHS, Qiang (Ed) Zhang, PhD	2019	Springer Publishing Company
Unsupervised Deep Learning Architectures	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	Advances in Deep Learning	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	1st ed. 2020	Springer Nature Singapore
Deep Unsupervised System Log Monitoring	Hubert Nourtel; Christophe Cerisara; Samuel Cruz-Lara	Product-Focused Software Process Improvement: 20th International Conference, PROFES 2019, Barcelona, Spain, November 27–29, 2019, Proceedings	Xavier Franch; Tomi Männistö; Silverio Martínez-Fernández	1st ed. 2019	Springer International Publishing
Unsupervised learning Clustering methods	Ernest Czogała; Jacek Łęski	Fuzzy and Neuro-Fuzzy Intelligent Systems	Ernest Czogala; Jacek Leski	2000	Physica-Verlag HD
Deep learning and unsupervised pretraining		Python: Real World Machine Learning	Prateek Joshi; Luca Massaron; John Hearty	2017	Packt Publishing
332 Unsupervised Deep Learning Models		Real-Time Cloud Computing and Machine Learning Applications	Tulsi Pawan Fowdur	2021	Nova Science Publishers, Inc.
Section 2: Unsupervised Deep Learning		Deep Learning for Beginners; A beginner's guide to getting up and running with deep learning from scratch using Python	Dr. Pablo Rivas	2020	Packt
Unsupervised Learning: Deep Generative Model	Chen Lei	Deep Learning and Practice with MindSpore	Lei Chen	1st ed. 2021	Springer Nature Singapore
4 Deep Autoencoders - Unsupervised Learning		Deep Learning: Methods and Applications	Li Deng, Dong Yu	2014	Now Publishers
722 Methods based on deep learning		Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, Technologies and Applications	Chiranji Lal Chowdhary (editor), Mamoun Alazab (editor), Ankit Chaudhary (editor), Saqib Hakak (editor), G. Thippa Reddy (editor)	2021	The Institution of Engineering and Technology
Chapter	Author(s)	Book	Book Authors	Year	Publisher

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