"On the Performance of Deep Learning Models for Time Series Classification in Streaming"

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Book	Author(s)	Year	Publisher
Deep Learning Models for Medical Imaging	KC Santosh; Nibaran Das and Swarnendu Ghosh	2021	Academic Press
Deep Learning for Hyperspectral Image Analysis and Classification	Linmi Tao; Atif Mughees	1st ed. 2021	Springer Nature Singapore
Stochastic Models for Time Series	Paul Doukhan	1st ed. 2018	Springer International Publishing
Models for Dependent Time Series	Granville Tunnicliffe Wilson; Marco Reale; John Haywood	2015	Routledge
Time series models /	Harvey, A. C.	1993.	MIT Press,
Time series models	A. C. Harvey	1981	Wiley
Time series models	A. C. Harvey	1981	Philip Allan Publishers Limited
Deep Learning for Natural Language Processing: Develop Deep Learning Models for your Natural Language Problems	Jason Brownlee	2017	Independently Published
Multivariate Tests for Time Series Models	Jeff B. Cromwell; Walter C. Labys; Michael J. Hannan; Michel Terraza	July 1994	SAGE Publications, Inc
Univariate Tests for Time Series Models	Jeff B. Cromwell; Walter C. Labys; Michel Terraza	December 1993	SAGE Publications, Inc
Regression Models for Time Series Analysis	Benjamin Kedem	2002	John Wiley & Sons
Univariate tests for time series models	Jeff B. Cromwell	1994	Sage Publications
Regression models for time series analysis /	Kedem, Benjamin,; Fokianos, Konstantinos.	[2002], ©2002.	John Wiley & Sons, Inc.,
Advanced Analytics and Deep Learning Models	Shaveta Malik; Amit Kumar Tyagi; Archana Mire	2022	John Wiley & Sons
Inside Deep Learning: Math, Algorithms, Models	Edward Raff	2022	Manning Publications
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch	Nikhil Ketkar; Jojo Moolayil	2nd ed.	Apress
Practical Machine Learning for Streaming Data with Python: Design, Develop, and Validate Online Learning Models	Sayan Putatunda	1st ed.	Apress
Periodic Time Series Models	Philip Hans Franses; Richard Paap	2004	Oxford University Press
Bayesian Time Series Models	David Barber; A. Taylan Cemgil; Silvia Chiappa	2011-08	Cambridge University Press
Multiple Time Series Models	Patrick T. Brandt; John T. Williams	September 2006	SAGE Publications, Inc
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
On the Performance of Deep Learning Models for Time Series Classification in Streaming	Pedro Lara-Benítez; Manuel Carranza-García; Francisco Martínez-Álvarez; José C. Riquelme	15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020)	Álvaro Herrero; Carlos Cambra; Daniel Urda; Javier Sedano; Héctor Quintián; Emilio Corchado	1st ed. 2021	Springer International Publishing
Deep Learning for Haemodialysis Time Series Classification	Giorgio Leonardi; Stefania Montani; Manuel Striani	Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems: AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26–29, 2019, Revised Selected Papers	Mar Marcos; Jose M. Juarez; Richard Lenz; Grzegorz J. Nalepa; Slawomir Nowaczyk; Mor Peleg; Jerzy Stefanowski; Gregor Stiglic	1st ed. 2019	Springer International Publishing
Deep learning for time series		Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods	Ben Auffarth	2021	Packt Publishing - ebooks Account
Deep Learning for Time Series	Taesam Lee; Vijay P. Singh; Kyung Hwa Cho	Deep Learning for Hydrometeorology and Environmental Science	Taesam Lee; Vijay P. Singh; Kyung Hwa Cho	1st ed. 2021	Springer International Publishing
Performance Analysis of Different Deep Learning Models for Forest Fire Classification	S. Harshaw Kamal; R. K. Ragul Raj; T. Sabari; R. Karthika	Disruptive Technologies for Big Data and Cloud Applications: Proceedings of ICBDCC 2021	J. Dinesh Peter; Steven Lawrence Fernandes; Amir H. Alavi	1st ed. 2022	Springer Nature Singapore
On the Performance of Deep Learning Models for Respiratory Sound Classification Trained on Unbalanced Data	Carlos Castorena; Francesc J. Ferri; Maximo Cobos	Pattern Recognition and Image Analysis: 10th Iberian Conference, IbPRIA 2022, Aveiro, Portugal, May 4–6, 2022, Proceedings	Armando J. Pinho; Petia Georgieva; Luís F. Teixeira; Joan Andreu Sánchez	1st ed. 2022	Springer International Publishing
Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning	Christian Bock; Michael Moor; Catherine R. Jutzeler; Karsten Borgwardt	Artificial Neural Networks	Hugh Cartwright	3rd ed. 2021	Springer US
Continuous Trend-Based Classification of Streaming Time Series	Maria Kontaki; Apostolos N. Papadopoulos; Yannis Manolopoulos	Advances in Databases and Information Systems: 9th East European Conference, ADBIS 2005, Tallinn, Estonia, September 12-15, 2005, Proceedings	Johann Eder; Hele-Mai Haav; Ahto Kalja; Jaan Penjam	2005	Springer Berlin Heidelberg
A Survey on Deep Learning for Time-Series Forecasting	Amal Mahmoud; Ammar Mohammed	Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges	Aboul Ella Hassanien; Ashraf Darwish	1st ed. 2021	Springer International Publishing
Promise of Deep Learning for Time Series Forecasting		Deep Learning for Time Series Forecasting - Predict the Future with MLPs, CNNs and LSTMs in Python	Jason Brownlee	2018
Deep Learning Techniques for Time Series Modelling	Paul Fergus; Carl Chalmers	Applied Deep Learning: Tools, Techniques, and Implementation	Paul Fergus; Carl Chalmers	1st ed. 2022	Springer International Publishing
3 Deep Learning for Time Series Modeling		Machine Learning for Financial Risk Management with Python: Algorithms for Modeling Risk	Abdullah Karasan	2022	O'Reilly Media
Chapter 10: Deep Learning for Time-Series		Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods	Ben Auffarth	2021	Packt Publishing - ebooks Account
Chapter 10: Deep learning for time series		Deep Learning with R	Francois Chollet, Tomasz Kalinowski, J. J. Allaire	2022	Manning
Deep Learning-Based Prediction, Classification, Clustering Models for Time Series Analysis: A Systematic Review	Nitesh N. Naik; K. Chandrasekaran; M. Venkatesan; P. Prabhavathy	Advances in Information Communication Technology and Computing: Proceedings of AICTC 2021	Vishal Goar; Manoj Kuri; Rajesh Kumar; Tomonobu Senjyu	1st ed. 2022	Springer Nature Singapore
On-Line Dynamic Time Warping for Streaming Time Series	Izaskun Oregi; Aritz Pérez; Javier Del Ser; José A. Lozano	Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part II	Michelangelo Ceci; Jaakko Hollmén; Ljupčo Todorovski; Celine Vens; Sašo Džeroski	1st ed. 2017	Springer International Publishing
Learning Causal Time Series Models		Elements of Causal Inference. Foundations and Learning Algorithms	Jonas Peters, Dominik Janzing, Bernhard Scholkopf	2017	The MIT Press
Deep Learning Models for 3D MRI Brain Classification	Marius Pullig; Benjamin Bergner; Amish Doshi; Anja Hennemuth; Zahi A. Fayad; Christoph Lippert	Bildverarbeitung für die Medizin 2022: Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022	Klaus Maier-Hein; Thomas M. Deserno; Heinz Handels; Andreas Maier; Christoph Palm; Thomas Tolxdorff	1. Aufl. 2022	Springer Fachmedien Wiesbaden
Hybrid Deep Learning Models for Diabetic Retinopathy Classification	Mounia Mikram; Chouaib Moujahdi; Maryem Rhanoui; Majdouline Meddad; Asmaa Khallout	Proceedings of the 5th International Conference on Big Data and Internet of Things	Mohamed Lazaar; Claude Duvallet; Abdellah Touhafi; Mohammed Al Achhab	1st ed. 2022	Springer International Publishing
Deep Learning-Based Time Series Forecasting	Kushagra Agarwal; Lalasa Dheekollu; Gaurav Dhama; Ankur Arora; Siddhartha Asthana; Tanmoy Bhowmik	Deep Learning Applications, Volume 3	M. Arif Wani; Bhiksha Raj; Feng Luo; Dejing Dou	1st ed. 2022	Springer Nature Singapore
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