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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

R, Pirich Andrew, and Society of Photo-optical Instrumentation Engineers., eds. Photonic component engineering and applications: 8-9 April 1996, Orlando, Florida. Bellingham, Wash: SPIE, 1996.

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12

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

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13

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

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14

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

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15

Brunner, Daniel, Miguel C. Soriano, and Guy Van der Sande. Photonic Reservoir Computing: Optical Recurrent Neural Networks. de Gruyter GmbH, Walter, 2019.

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16

Brunner, Daniel, Miguel C. Soriano, and Guy Van der Sande. Photonic Reservoir Computing: Optical Recurrent Neural Networks. de Gruyter GmbH, Walter, 2019.

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17

Brunner, Daniel, Miguel C. Soriano, and Guy Van der Sande. Photonic Reservoir Computing: Optical Recurrent Neural Networks. de Gruyter GmbH, Walter, 2019.

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18

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

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19

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

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20

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

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21

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

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22

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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23

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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24

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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25

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

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26

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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27

Vittorio, Massimo De, Luigi Martiradonna, and John Assad. Nanotechnology and Neuroscience: Nano-electronic, Photonic and Mechanical Neuronal Interfacing. Springer, 2014.

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28

Vittorio, Massimo De, Luigi Martiradonna, and John Assad. Nanotechnology and Neuroscience: Nano-electronic, Photonic and Mechanical Neuronal Interfacing. Springer, 2016.

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29

Vittorio, Massimo De, Luigi Martiradonna, and John Assad. Nanotechnology and Neuroscience: Nano-Electronic, Photonic and Mechanical Neuronal Interfacing. Springer London, Limited, 2014.

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30

Photonic Neuromorphic Computing. Taylor & Francis Group, 2017.

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31

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

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32

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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33

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

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34

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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35

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

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36

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

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37

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

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38

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

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39

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

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40

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

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41

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

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42

Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks. Apress, 2018.

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43

Michelucci, Umberto. Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks. Apress / KP, 2019.

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44

Deep Learning with TensorFlow: Explore neural networks with Python. Packt Publishing, 2017.

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45

Suresh, Annamalai, R. Udendran, and S. Vimal. Deep Neural Networks for Multimodal Imaging and Biomedical Applications. IGI Global, 2020.

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46

Suresh, Annamalai, R. Udendran, and S. Vimal. Deep Neural Networks for Multimodal Imaging and Biomedical Applications. IGI Global, 2020.

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47

Vidales, A. Deep Learning with Matlab: Big Data and Neural Networks. Independently Published, 2018.

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48

Vidales, A. Deep Learning with Matlab: Neural Networks Tools and Functions. Independently Published, 2018.

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49

Suresh, Annamalai, R. Udendran, and S. Vimal. Deep Neural Networks for Multimodal Imaging and Biomedical Applications. IGI Global, 2020.

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50

Zhang, Yunong, Dechao Chen, and Chengxu Ye. Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications. Taylor & Francis Group, 2019.

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