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1

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

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2

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

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3

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

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4

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

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5

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

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6

Caterini, Anthony L., and 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.

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7

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

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8

Fingscheidt, Tim, Hanno Gottschalk, and 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.

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9

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.

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10

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

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11

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.

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12

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

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13

Lu, Le, Yefeng Zheng, Gustavo Carneiro, and 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.

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14

Tetko, Igor V., Věra Kůrková, Pavel Karpov, and 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.

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15

H, Szu Harold, International Neural Network Society, and 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.

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16

Szu, Harold H., and 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.

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17

H, Szu Harold, Society of Photo-optical Instrumentation Engineers., and 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.

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18

H, Szu Harold, Agee Jack, and 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.

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19

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.

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20

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

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21

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

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22

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

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23

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

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24

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

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25

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

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26

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

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27

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

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28

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

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29

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

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30

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

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31

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

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32

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

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33

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

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34

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

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35

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

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36

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

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37

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

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38

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

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39

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

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40

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

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41

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

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42

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

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43

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

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44

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

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45

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

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46

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

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47

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

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48

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

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49

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

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50

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

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