Книги з теми "Deep Photonic Neural Networks"

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., 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.

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, 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.

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.

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.

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.

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.

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.

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Photonic Neuromorphic Computing. Taylor & Francis Group, 2017.

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

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.

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

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

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

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.

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

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

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

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

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

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

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

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

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