Neural Network Models In Artificial Intelligence
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Neural Network Models In Artificial Intelligence
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Author : Matthew Zeidenberg
language : en
Publisher: Ellis Horwood
Release Date : 1990
Neural Network Models In Artificial Intelligence written by Matthew Zeidenberg and has been published by Ellis Horwood this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
The aim of this book is to provide a concise introduction to recent, representative work in the field of neural networks. Each topic provides an overview of work in one particular area and proceeds towards a review of current research and development in that area.
Artificial Neural Networks
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Author : Joao Luis Garcia Rosa
language : en
Publisher: BoD – Books on Demand
Release Date : 2016-10-19
Artificial Neural Networks written by Joao Luis Garcia Rosa and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-19 with Computers categories.
The idea of simulating the brain was the goal of many pioneering works in Artificial Intelligence. The brain has been seen as a neural network, or a set of nodes, or neurons, connected by communication lines. Currently, there has been increasing interest in the use of neural network models. This book contains chapters on basic concepts of artificial neural networks, recent connectionist architectures and several successful applications in various fields of knowledge, from assisted speech therapy to remote sensing of hydrological parameters, from fabric defect classification to application in civil engineering. This is a current book on Artificial Neural Networks and Applications, bringing recent advances in the area to the reader interested in this always-evolving machine learning technique.
Neural Networks In Artificial Intelligence
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Author : Matthew Zeidenberg
language : en
Publisher:
Release Date : 1991
Neural Networks In Artificial Intelligence written by Matthew Zeidenberg and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Artificial intelligence categories.
A Comprehensive Guide To Neural Network Modeling
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Author : Steffen Skaar
language : en
Publisher: Nova Science Publishers
Release Date : 2020-10-26
A Comprehensive Guide To Neural Network Modeling written by Steffen Skaar and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-26 with Computers categories.
As artificial neural networks have been gaining importance in the field of engineering, this compilation aims to review the scientific literature regarding the use of artificial neural networks for the modelling and optimization of food drying processes. The applications of artificial neural networks in food engineering are presented, particularly focusing on control, monitoring and modeling of industrial food processes.The authors emphasize the main achievements of artificial neural network modeling in recent years in the field of quantitative structure-activity relationships and quantitative structure-retention relationships.In the closing study, artificial intelligence techniques are applied to river water quality data and artificial intelligence models are developed in an effort to contribute to the reduction of the cost of future on-line measurement stations.
Artificial Neural Networks Models And Applications
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Author :
language : en
Publisher:
Release Date : 19??
Artificial Neural Networks Models And Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 19?? with categories.
Machine Learning And Artificial Intelligence
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Author : Antonio J. Tallón-Ballesteros
language : en
Publisher: SAGE Publications Limited
Release Date : 2020-12-15
Machine Learning And Artificial Intelligence written by Antonio J. Tallón-Ballesteros and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-15 with Computers categories.
Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.
Deep Learning With Pytorch
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Author : Vishnu Subramanian
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-23
Deep Learning With Pytorch written by Vishnu Subramanian and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-23 with Computers categories.
Build neural network models in text, vision and advanced analytics using PyTorch Key Features Learn PyTorch for implementing cutting-edge deep learning algorithms. Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Book Description Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images. By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease. What you will learn Use PyTorch for GPU-accelerated tensor computations Build custom datasets and data loaders for images and test the models using torchvision and torchtext Build an image classifier by implementing CNN architectures using PyTorch Build systems that do text classification and language modeling using RNN, LSTM, and GRU Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning Learn how to mix multiple models for a powerful ensemble model Generate new images using GAN’s and generate artistic images using style transfer Who this book is for This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected.
Artificial Intelligence For Ehealth
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Author : Deepak Gupta
language : en
Publisher: Frontiers Media SA
Release Date : 2022-04-25
Artificial Intelligence For Ehealth written by Deepak Gupta and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-25 with Medical categories.
Estimating Ore Grade Using Evolutionary Machine Learning Models
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Author : Mohammad Ehteram
language : en
Publisher: Springer Nature
Release Date : 2022-12-27
Estimating Ore Grade Using Evolutionary Machine Learning Models written by Mohammad Ehteram and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Science categories.
This book examines the abilities of new machine learning models for predicting ore grade in mining engineering. A variety of case studies are examined in this book. A motivation for preparing this book was the absence of robust models for estimating ore grade. Models of current books can also be used for the different sciences because they have high capabilities for estimating different variables. Mining engineers can use the book to determine the ore grade accurately. This book helps identify mineral-rich regions for exploration and exploitation. Exploration costs can be decreased by using the models in the current book. In this book, the author discusses the new concepts in mining engineering, such as uncertainty in ore grade modeling. Ensemble models are presented in this book to estimate ore grade. In the book, readers learn how to construct advanced machine learning models for estimating ore grade. The authors of this book present advanced and hybrid models used to estimate ore grade instead of the classic methods such as kriging. The current book can be used as a comprehensive handbook for estimating ore grades. Industrial managers and modelers can use the models of the current books. Each level of ore grade modeling is explained in the book. In this book, advanced optimizers are presented to train machine learning models. Therefore, the book can also be used by modelers in other fields. The main motivation of this book is to address previous shortcomings in the modeling process of ore grades. The scope of this book includes mining engineering, soft computing models, and artificial intelligence.
Brain Networks In Neuroscience Personalization Unveiled Via Artificial Intelligence
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Author : Md. Mehedi Hassan
language : en
Publisher: CRC Press
Release Date : 2025-07-03
Brain Networks In Neuroscience Personalization Unveiled Via Artificial Intelligence written by Md. Mehedi Hassan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-03 with Science categories.
This book is an in-depth exploration of brain networks, providing a comprehensive understanding of their structures, functions, and implications for personalization through artificial intelligence. Readers will gain insights into the intricate workings of the brain, making this book an indispensable resource for those seeking a thorough grasp of neuroscience concepts. It offers the seamless integration of neuroscience principles with artificial intelligence applications. The book bridges these two domains, elucidating how advancements in AI draw inspiration from the complexities of the human brain. This interdisciplinary approach sets the book apart, offering readers a holistic view of cutting-edge technologies. Readers can expect practical applications and real-world case studies that illustrate the tangible benefits of the concepts discussed. From personalized healthcare solutions to adaptive learning systems, the book goes beyond theory, empowering readers to apply knowledge in diverse domains. This practical emphasis enhances the book’s relevance for professionals and researchers alike. The inclusion of online enhancements, such as interactive visualizations, downloadable supplementary materials, and engaging video content, transforms the reading experience into an interactive learning journey. This added value distinguishes the book by providing readers with hands-on tools to deepen their understanding and apply newfound knowledge. This book doesn’t just dwell on current technologies; it takes readers into the future by exploring emerging trends at the intersection of neuroscience and artificial intelligence. By delving into potential breakthroughs and innovations, the book equips readers with insights that are forward-thinking and relevant in an ever-evolving technological landscape.