"Deep Learning Architectures Applied to Mosquito Count Regressions in US Datasets"

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Book	Author(s)	Year	Publisher
Deep Learning: Concepts and Architectures	Witold Pedrycz; Shyi-Ming Chen	1st ed. 2020	Springer International Publishing
Hardware Architectures for Deep Learning	Masoud Daneshtalab (editor), Mehdi Modarressi (editor)	2020	INSTITUTION OF ENGINEERING & T
Deep In-memory Architectures for Machine Learning	Mingu Kang; Sujan Gonugondla; Naresh R. Shanbhag	1st ed. 2020	Springer International Publishing
Deep Learning Architectures: A Mathematical Approach	Ovidiu Calin	1st ed. 2020	Springer International Publishing
Development and Analysis of Deep Learning Architectures	Witold Pedrycz; Shyi-Ming Chen	1st ed. 2020	Springer International Publishing
Applied Deep Learning with Python	Alex Galea, Luis Capelo	2018	Packt Publishing
Math and Architectures of Deep Learning Version 10	Krishnendu Chaudhury	2021	Manning Publications
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks	Umberto Michelucci	1st ed.	Apress
Applied Deep Learning with TensorFlow 2: Learn to Implement Advanced Deep Learning Techniques with Python	Umberto Michelucci	2nd ed.	Apress
Applied Deep Learning: Tools, Techniques, and Implementation	Paul Fergus; Carl Chalmers	1st ed. 2022	Springer International Publishing
Count on us!	A. A. Milne	2008	Parragon
Count on us!	Walt Disney Company	2007	Creative Edge, LLC;distributed by Greenbrier International, Inc.
Starting to Count (First Learning)	Jenny Tyler	January 1988	Educational Development Corporation
Learning To Count (Maxi Peekaboo)	Yoyo	November 25, 2005	Yoyo Books
The TensorFlow Workshop: A hands-on guide to building deep learning models from scratch using real-world datasets	Matthew Moocarme	2021	Packt Publishing - ebooks Account
Hands-On Deep Learning Architectures with Python: Create deep neural networks to solve computational problems using TensorFlow and Keras	Yuxi (Hayden) Liu, Saransh Mehta	2019	Packt Publishing
Deep Learning in Science	Pierre Baldi	2021-07	Cambridge University Press
Advances in Deep Learning	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	1st ed. 2020	Springer Nature Singapore
Deep Learning in Biometrics	Mayank Vatsa; Richa Singh; Angshul Majumdar	2018	Routledge
Deep Learning in Bioinformatics	Habib Izadkhah	2022	Academic Press
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Deep Learning Architectures Applied to Mosquito Count Regressions in US Datasets	Cuauhtemoc Daniel Suarez-Ramirez; Mario Alberto Duran-Vega; Hector M. Sanchez C.; Miguel Gonzalez-Mendoza; Leonardo Chang; John M. Marshall	Advances in Computational Intelligence: 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, Mexico City, Mexico, October 25–30, 2021, Proceedings, Part I	Ildar Batyrshin; Alexander Gelbukh; Grigori Sidorov	1st ed. 2021	Springer International Publishing
Deep Learning Architectures		Encyclopedia of Computational Neuroscience	Dieter Jäger; Ranu Jung	2nd ed. 2022	Springer New York
Deep Learning Architectures		Reinforcement Learning: Industrial Applications of Intelligent Agents	Phil Winder	2020	O'Reilly Media
Deep Learning Architectures		Tensorflow for Deep Learning: From Linear Regression to Reinforcement Learning	Bharath Ramsundar	2018	O'Reilly Media
Deep Learning Architectures	Mohammad-Parsa Hosseini; Senbao Lu; Kavin Kamaraj; Alexander Slowikowski; Haygreev C. Venkatesh	Deep Learning: Concepts and Architectures	Witold Pedrycz; Shyi-Ming Chen	1st ed. 2020	Springer International Publishing
Supervised Deep Learning Architectures	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	Advances in Deep Learning	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	1st ed. 2020	Springer Nature Singapore
Unsupervised Deep Learning Architectures	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	Advances in Deep Learning	M. Arif Wani; Farooq Ahmad Bhat; Saduf Afzal; Asif Iqbal Khan	1st ed. 2020	Springer Nature Singapore
63 Deep Learning Architectures		Cyber-Physical Systems: Foundations and Techniques	Uzzal Sharma (editor), Parma Nand (editor), Jyotir Moy Chatterjee (editor), Vishal Jain (editor), Noor Zaman Jhanjhi (editor), R. Sujatha (editor)	2022	Wiley-Scrivener
Deep learning from small labeled datasets applied to medical image analysis	Harini Veeraraghavan; Jue Jiang	State of the Art in Neural Networks and their Applications	Ayman S. El-Baz and Jasjit S. Suri	2021	Academic Press
Deep Learning for Spatial Datasets	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
Deep Learning with TensorFlow Datasets	David Paper	State-of-the-Art Deep Learning Models in TensorFlow: Modern Machine Learning in the Google Colab Ecosystem	David Paper	1st ed.	Apress
Extreme Heterogeneity in Deep Learning Architectures	Jeff Anderson; Armin Mehrabian; Jiaxin Peng; Tarek El-Ghazawi	Smart Data: State-of-the-Art Perspectives in Computing and Applications	Kuan-Ching Li; Beniamino Di Martino; Laurence T. Yang; Qingchen Zhang	2018	Routledge
Deep Architectures in Visual Transfer Learning	Walid Gomaa	Vision, Sensing and Analytics: Integrative Approaches	Md Atiqur Rahman Ahad; Atsushi Inoue	1st ed. 2021	Springer International Publishing
Deep Learning Applied to Deep Brain Stimulation in Parkinson’s Disease	Pablo Guillén	High Performance Computing: Third Latin American Conference, CARLA 2016, Mexico City, Mexico, August 29–September 2, 2016, Revised Selected Papers	Carlos Jaime Barrios Hernández; Isidoro Gitler; Jaime Klapp	1st ed. 2017	Springer International Publishing
Deep Learning Applied to Deep Brain Stimulation in Parkinson’s Disea		High Performance Computing	Carlos Jaime Barrios Hernandez, Isidoro Gitler, Jaime Klapp (eds.)	2017	Springer
Deep learning architectures for IoT		Hands-on deep learning for IoT: train neural network models to develop intelligent IoT applications	Karim, Md. Rezaul; Razzaque, Mohammad Abdur	2019	Packt Publishing
Section 2: Deep Learning Architectures		Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch	Shruti Jadon, Ankush Garg	2020	Packt Publishing
3 Understanding Deep Learning Architectures		Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras	Dipanjan Sarkar; Raghav Bali; Tamoghna Ghosh	2018	Packt Publishing
103 Other count regressions		Statistical Rethinking	Richard McElreath	2015-12-18	Chapman & Hall/CRC
Count Us In		A son's return: selected essays of Sterling A. Brown /	Brown, Sterling A.,; Sanders, Mark A.,	[1996], ©1996.	Northeastern University Press,
Chapter	Author(s)	Book	Book Authors	Year	Publisher

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