Libros sobre el tema "Unsupervised deep neural networks"

E, Hinton Geoffrey y Sejnowski Terrence J, eds. Unsupervised learning: Foundations of neural computation. Cambridge, Mass: MIT Press, 1999.

Baruque, Bruno. Fusion methods for unsupervised learning ensembles. Berlin: Springer, 2010.

Aggarwal, Charu C. Neural Networks and Deep Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94463-0.

Aggarwal, Charu C. Neural Networks and Deep Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29642-0.

Moolayil, Jojo. Learn Keras for Deep Neural Networks. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4240-7.

Caterini, Anthony L. y Dong Eui Chang. Deep Neural Networks in a Mathematical Framework. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75304-1.

Razaghi, Hooshmand Shokri. Statistical Machine Learning & Deep Neural Networks Applied to Neural Data Analysis. [New York, N.Y.?]: [publisher not identified], 2020.

Fingscheidt, Tim, Hanno Gottschalk y Sebastian Houben, eds. Deep Neural Networks and Data for Automated Driving. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-01233-4.

Modrzyk, Nicolas. Real-Time IoT Imaging with Deep Neural Networks. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5722-7.

Supervised and unsupervised pattern recognition: Feature extraction and computational intelligence. Boca Raton, Fla: CRC Press, 2000.

Iba, Hitoshi. Evolutionary Approach to Machine Learning and Deep Neural Networks. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0200-8.

Whitehead, P. A. Design considerations for a hardware accelerator for Kohonen unsupervised learning in artificial neural networks. Manchester: UMIST, 1997.

Lu, Le, Yefeng Zheng, Gustavo Carneiro y Lin Yang, eds. Deep Learning and Convolutional Neural Networks for Medical Image Computing. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-42999-1.

Tetko, Igor V., Věra Kůrková, Pavel Karpov y Fabian Theis, eds. Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30484-3.

H, Szu Harold, International Neural Network Society y IEEE Neural Networks Society, eds. Independent component analyses, wavelets, unsupervised smart sensors, and neural networks II: 14-15 April 2004, Orlando, Florida, USA. Bellingham, Wash., USA: SPIE, 2004.

Szu, Harold H. y Jack Agee. Independent component analyses, wavelets, unsupervised nano-biomimetic sensors, and neural networks VI: 17-19 March 2008, Orlando, Florida, USA. Bellingham, Wash: SPIE, 2008.

H, Szu Harold, Society of Photo-optical Instrumentation Engineers. y Ball Aerospace & Technologies Corporation (USA), eds. Independent component analyses, wavelets, unsupervised smart sensors, and neural networks III: 30 March-1 April, 2005, Orlando, Florida, USA. Bellingham, Wash: SPIE, 2005.

H, Szu Harold, Agee Jack y Society of Photo-optical Instrumentation Engineers., eds. Independent component analyses, wavelets, unsupervised nano-biomimetic sensors, and neural networks V: 10-13 April 2007, Orlando, Florida, USA. Bellingham, Wash: SPIE, 2007.

Leordeanu, Marius. Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision Using Graph-Based Techniques and Deep Neural Networks. Springer International Publishing AG, 2021.

Leordeanu, Marius. Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks. Springer, 2020.

Zhang, Yunong, Dechao Chen y Chengxu Ye. Deep Neural Networks. Taylor & Francis Group, 2020.

Sejnowski, Terrence J. y Geoffrey Hinton. Unsupervised Learning: Foundations of Neural Computation. MIT Press, 1999.

Sejnowski, Terrence J., Tomaso A. Poggio y Geoffrey Hinton. Unsupervised Learning: Foundations of Neural Computation. MIT Press, 2016.

Graupe, Daniel. Deep Learning Neural Networks. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/10190.

Nakamoto, Pat. Neural Networks and Deep Learning: Neural Networks & Deep Learning, Deep Learning, Blockchain Blueprint. Createspace Independent Publishing Platform, 2018.

Baruque, Bruno. Fusion Methods for Unsupervised Learning Ensembles. Springer, 2010.

Baruque, Bruno. Fusion Methods for Unsupervised Learning Ensembles. Springer, 2014.

(Editor), Geoffrey Hinton y Terrence J. Sejnowski (Editor), eds. Unsupervised Learning: Foundations of Neural Computation (Computational Neuroscience). The MIT Press, 1999.

Stanimirovic, Ivan. Deep Neural Networks and Applications. Arcler Education Inc, 2019.

Davis, Ronald. Neural Networks and Deep Learning. Independently Published, 2017.

Stanimirovic, Ivan. Deep Neural Networks and Applications. Arcler Education Inc, 2019.

Becker, Helen Suzanna. An information-theoretic unsupervised learning algorithm for neural networks. 1993.

Vidales, A. Deep Learning with Matlab: Neural Networks Design and Dynamic Neural Networks. Independently Published, 2018.

Sze, Vivienne, Yu-Hsin Chen, Tien-Ju Yang y Joel S. Emer. Efficient Processing of Deep Neural Networks. Morgan & Claypool Publishers, 2020.

Strong, Christopher, Clark Barrett, Changliu Liu, Tomer Arnon y Christopher Lazarus. Algorithms for Verifying Deep Neural Networks. Now Publishers, 2021.

Sze, Vivienne, Yu-Hsin Chen, Tien-Ju Yang y Joel S. Emer. Efficient Processing of Deep Neural Networks. Morgan & Claypool Publishers, 2020.

Sze, Vivienne, Yu-Hsin Chen, Tien-Ju Yang y Joel S. Emer. Efficient Processing of Deep Neural Networks. Springer International Publishing AG, 2020.

Sze, Vivienne, Yu-Hsin Chen, Tien-Ju Yang y Joel S. Emer. Efficient Processing of Deep Neural Networks. Morgan & Claypool Publishers, 2020.

Neural Networks and Deep Learning: A Textbook. Springer, 2018.

Luigi Mazzeo, Pier, Srinivasan Ramakrishnan y Paolo Spagnolo, eds. Visual Object Tracking with Deep Neural Networks. IntechOpen, 2019. http://dx.doi.org/10.5772/intechopen.80142.

Chang, Dong Eui y Anthony L. L. Caterini. Deep Neural Networks in a Mathematical Framework. Springer, 2018.

Visual Object Tracking with Deep Neural Networks. IntechOpen, 2019.

Sugomori, Yusuke, Bostjan Kaluza, Fabio M. Soares y Alan M. F. Souza. Deep Learning: Practical Neural Networks with Java. Packt Publishing, 2017.

Aggarwal, Charu C. Neural Networks and Deep Learning: A Textbook. Springer, 2019.

Spencer, Quinn. Neural Networks: Deep Learning and Machine Learning Outlined. Independently Published, 2018.

Evolutionary Deep Learning: Genetic Algorithms and Neural Networks. Manning Publications Co. LLC, 2022.

Graupe, Daniel. Deep Learning Neural Networks: Design and Case Studies. World Scientific Publishing Co Pte Ltd, 2016.

Lopez, César Perez. DEEP LEARNING with MATLAB. NEURAL NETWORKS by EXAMPLES. Lulu Press, Inc., 2020.

Graupe, Daniel. Principles of Artificial Neural Networks: Basic Designs to Deep Learning. World Scientific Publishing Co Pte Ltd, 2019.

Campin, Michael James. Sigma-Delta modulator fault diagnosis using an unsupervised expert network. 1992.