"Predicting Hot Spots Using a Deep Neural Network Approach"

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Book	Author(s)	Year	Publisher
Predicting the Lineage Choice of Hematopoietic Stem Cells: A Novel Approach Using Deep Neural Networks	Manuel Kroiss	1st ed. 2016	Springer Fachmedien Wiesbaden
Deep learning with PyTorch: a practical approach to building neural network models using PyTorch	Subramanian, Vishnu	2018	Packt Publishing.
Deep learning with PyTorch: a practical approach to building neural network models using PyTorch	Subramanian, Vishnu	2018	Packt Publishing
Deep Neural Network Applications	Hasmik Osipyan; Bosede Iyiade Edwards; Adrian David Cheok	2022	Routledge
Network Intrusion Detection using Deep Learning: A Feature Learning Approach	Kwangjo Kim; Muhamad Erza Aminanto; Harry Chandra Tanuwidjaja	1st ed. 2018	Springer Nature Singapore
Neural network analysis using Simulnet	Edward J. Rzempoluck	1998	Springer
Deep-water Coral Reefs: Unique Biodiversity Hot-Spots	Martin Hovland	2008	Springer Netherlands
Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras	Vaibhav Verdhan	1st ed.	Apress
Hot spots	Anita Ganeri	2011	A. & C. Black
Deep neural network design for radar applications	Gurbuz, Sevgi Zubeyde		Institution of Engineering & Technology
Deep Neural Network Design for Radar Applications	Sevgi Zubeyde Gurbuz	2021	SciTech Publishing
Deep Learning Projects Using TensorFlow 2: Neural Network Development with Python and Keras	Vinita Silaparasetty	1st ed.	Apress
Automated Deep Learning Using Neural Network Intelligence: Develop and Design PyTorch and TensorFlow Models Using Python	Ivan Gridin	1st ed.	Apress
Nonlinear Identification and Control: A Neural Network Approach	G.P. Liu	2001	Springer London
Animal learning and cognition: a neural network approach /	Schmajuk, Nestor A.	1997.	Cambridge University Press,
Neural Network Data Analysis Using Simulnet™	Edward J. Rzempoluck	1998	Springer New York
Pyramid. Hot Spots	Steve Jackson	2018	Steve Jackson Games Incorporated
Modular learning in neural networks: a modularized approach to neural network classification	Tomas Hrycej	1992	Wiley
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks	Umberto Michelucci	1st ed.	Apress
Strategies for Feedback Linearisation: A Dynamic Neural Network Approach	Freddy Rafael Garces; Victor Manuel Becerra; Chandrasekhar Kambhampati; Kevin Warwick	2003	Springer London
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Predicting Hot Spots Using a Deep Neural Network Approach	António J. Preto; Pedro Matos-Filipe; José G. de Almeida; Joana Mourão; Irina S. Moreira	Artificial Neural Networks	Hugh Cartwright	3rd ed. 2021	Springer US
Predicting facial key points using a deep neural network		Mastering Computer Vision with TensorFlow 2. x: Build advanced computer vision applications using machine learning and deep learning techniques	Krishnendu Kar	2020	Packt Publishing
Anti-spoofing Approach Using Deep Convolutional Neural Network	Prosenjit Chatterjee; Kaushik Roy	Recent Trends and Future Technology in Applied Intelligence: 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2018, Montreal, QC, Canada, June 25-28, 2018, Proceedings	Malek Mouhoub; Samira Sadaoui; Otmane Ait Mohamed; Moonis Ali	1st ed. 2018	Springer International Publishing
Predicting conformers of flexible metal complexes using deep neural network	Hiroshi Sakiyama	Computational and Data-Driven Chemistry Using Artificial Intelligence	Takashiro Akitsu	2021	Elsevier
Implementing a deep neural network using MXNet		Deep Learning with R Cookbook: Over 45 unique recipes to delve into neural network techniques using R 3. 5. x	Swarna Gupta; Rehan Ali Ansari; Dipayan Sarkar	2020	Packt Publishing Ltd
Training a deep neural network using Keras		MACHINE LEARNING FOR OPENCV 4: intelligent algorithms for building image processing apps. . . using opencv 4, python, and scikit-learn, 2nd edit.	ADITYA SHRIMALI VISHWESH RAVI BEYELER MICHAEL SHARMA	2019	PACKT PUBLISHING LIMITED
Deep Neural Network	Jen-Tzung Chien	Source Separation and Machine Learning	Jen-Tzung Chien	2019	Academic Press
Deep Neural Network		Financial, Macro and Micro Econometrics Using R: Volume 42	C. R. Rao (editor), Hrishikesh D. Vinod (editor)	2020	North-Holland
Deep neural network		Learning Quantitative Finance with R	Jeet, Parem and Vats, Prashant	2017	Packt Publishing
Deep neural network		The perfect police state: an undercover odyssey into China's terrifying surveillance dystopia of the future	Cain, Geoffrey,		PublicAffairs
Deep Neural Network		Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning	Valliappa Lakshmanan	2022	O'Reilly Media
Predicting Bacterial Community Assemblages Using an Artificial Neural Network Approach	Peter Larsen; Yang Dai; Frank R. Collart	Artificial Neural Networks	Hugh Cartwright	2nd ed. 2015	Springer New York
Diabetes Detection Using Deep Neural Network	Saumendra Kumar Mohapatra; Susmita Nanda; Mihir Narayan Mohanty	Soft Computing Systems: Second International Conference, ICSCS 2018, Kollam, India, April 19–20, 2018, Revised Selected Papers	Ivan Zelinka; Roman Senkerik; Ganapati Panda; Padma Suresh Lekshmi Kanthan	1st ed. 2018	Springer Nature Singapore
Fault Prediction Using Deep Neural Network	Avishikta Chatterjee; Kulamala Vinod Kumar; Durga Prasad Mohapatra	Internet of Things and Connected Technologies: Conference Proceedings on 5th International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2020	Rajiv Misra; Nishtha Kesswani; Muttukrishnan Rajarajan; Veeravalli Bharadwaj; Ashok Patel	1st ed. 2021	Springer International Publishing
Rainfall Prediction Using Deep Neural Network	Chitra Desai	Communication and Intelligent Systems: Proceedings of ICCIS 2020	Harish Sharma; Mukesh Kumar Gupta; G. S. Tomar; Wang Lipo	1st ed. 2021	Springer Nature Singapore
A Computational Intelligence Approach Using SMOTE and Deep Neural Network (DNN)	Madhusmita Sahu; Rasmita Dash	Intelligent and Cloud Computing: Proceedings of ICICC 2021	Debahuti Mishra; Rajkumar Buyya; Prasant Mohapatra; Srikanta Patnaik	1st ed. 2022	Springer Nature Singapore
Predicting Customer Churn Using Artificial Neural Network	Sanjay Kumar; Manish Kumar	Engineering Applications of Neural Networks: 20th International Conference, EANN 2019, Xersonisos, Crete, Greece, May 24-26, 2019, Proceedings	John Macintyre; Lazaros Iliadis; Ilias Maglogiannis; Chrisina Jayne	1st ed. 2019	Springer International Publishing
Predicting Software Reliability with a Novel Neural Network Approach	Shirin Noekhah; Naomie Binti Salim; Nor Hawaniah Zakaria	Recent Trends in Information and Communication Technology: Proceedings of the 2nd International Conference of Reliable Information and Communication Technology (IRICT 2017)	Faisal Saeed; Nadhmi Gazem; Srikanta Patnaik; Ali Saleh Saed Balaid; Fathey Mohammed	1st ed. 2018	Springer International Publishing
Analyzing and predicting images through a neural network approach	L. de Braal; N. Ezquerra; E. Schwartz; C. D. Cooke; E. Garcia	Visualization in Biomedical Computing: 4th International Conference, VBC ' 96, Hamburg, Germany, September 22 - 25, 1996, Proceedings	Karl H. Höhne; Ron Kikinis	1996	Springer Berlin Heidelberg
A Neural Network Approach to Predicting Stock Exchange Movements using External Factors	Niall O’Connor; Michael G. Madden	Applications and Innovations in Intelligent Systems XIII: Proceedings of AI2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artifical Intelligence	Ann Macintosh; Richard Ellis; Tony Allen	2006	Springer London
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Showing 1 to 20 of 100 entries

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