Building Feature Extraction With Machine Learning

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Building Feature Extraction with Machine Learning

Bharath.H. Aithal,Prakash P.S.

Author : Bharath.H. Aithal,Prakash P.S.
Publisher : CRC Press
Page : 109 pages
File Size : 41,7 Mb
Release : 2022-12-29
Category : Technology & Engineering
ISBN : 9781000817201

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Building Feature Extraction with Machine Learning by Bharath.H. Aithal,Prakash P.S. Pdf

Big geospatial datasets created by large infrastructure projects require massive computing resources to process. Feature extraction is a process used to reduce the initial set of raw data for manageable image processing, and machine learning (ML) is the science that supports it. This book focuses on feature extraction methods for optical geospatial data using ML. It is a practical guide for professionals and graduate students who are starting a career in information extraction. It explains spatial feature extraction in an easy-to-understand way and includes real case studies on how to collect height values for spatial features, how to develop 3D models in a map context, and others. Features Provides the basics of feature extraction methods and applications along with the fundamentals of machine learning Discusses in detail the application of machine learning techniques in geospatial building feature extraction Explains the methods for estimating object height from optical satellite remote sensing images using Python Includes case studies that demonstrate the use of machine learning models for building footprint extraction and photogrammetric methods for height assessment Highlights the potential of machine learning and geospatial technology for future project developments This book will be of interest to professionals, researchers, and graduate students in geoscience and earth observation, machine learning and data science, civil engineers, and urban planners.

Remote Sensing Based Building Extraction

Mohammad Awrangjeb,Xiangyun Hu,Bisheng Yang,Jiaojiao Tian

Author : Mohammad Awrangjeb,Xiangyun Hu,Bisheng Yang,Jiaojiao Tian
Publisher : MDPI
Page : 442 pages
File Size : 45,6 Mb
Release : 2020-03-27
Category : Science
ISBN : 9783039283828

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Remote Sensing Based Building Extraction by Mohammad Awrangjeb,Xiangyun Hu,Bisheng Yang,Jiaojiao Tian Pdf

Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D

Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book

Reza Forghani

Author : Reza Forghani
Publisher : Elsevier Health Sciences
Page : 192 pages
File Size : 50,9 Mb
Release : 2020-10-23
Category : Medical
ISBN : 9780323712453

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Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book by Reza Forghani Pdf

This issue of Neuroimaging Clinics of North America focuses on Artificial Intelligence and Machine Learning and is edited by Dr. Reza Forghani. Articles will include: A Brief History of Artificial Intelligence; Evolution of Approaches for Computerized Image Analysis; Overview of Machine Learning Part 1: Classic Approaches; Overview of Machine Learning Part 2: Artificial Neural Networks & Deep Learning; Overview of Natural Language Processing; Artificial Intelligence & Stroke Imaging: An East Coast Perspective; Artificial Intelligence & Stroke Imaging: A West Coast Perspective; Artificial Intelligence Applications for Brain Tumor Imaging; Diverse Applications of Artificial Intelligence in Neuroradiology; Artificial Intelligence Applications for Head and Neck Imaging; Artificial Intelligence Applications for Predictive Analytics and Workflow Optimization; Artificial Intelligence, Advanced Visualization, and 3D Printing; Ethical & Legal Considerations for Artificial Intelligence; Comprehensive (or 360) Artificial Intelligence: Beyond Image Interpretation Alone, and more!

Advances in Noise Reduction and Feature Extraction of Acoustic Signal

Govind Vashishtha,Rajesh Kumar

Author : Govind Vashishtha,Rajesh Kumar
Publisher : Frontiers Media SA
Page : 134 pages
File Size : 41,6 Mb
Release : 2023-10-11
Category : Science
ISBN : 9782832535783

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Advances in Noise Reduction and Feature Extraction of Acoustic Signal by Govind Vashishtha,Rajesh Kumar Pdf

Acoustic signal is one of the hot topics of research in physics and has been studied by many engineers and scientists in various real-world fields, including underwater acoustics, architectural acoustics, engineering acoustics, physical acoustics, environmental acoustics, psychological acoustics, and so on. Noise reduction is the foundation of acoustic signal pre-processing, and the feature extraction for noise reduction signals can obtain useful information from the acoustic signal, which is the linchpin for pattern recognition, target detection, tracking, and localization.

PRICAI 2012: Trends in Artificial Intelligence

Patricia Anthony,Mitsuru Ishizuka,Dickson Lukose

Author : Patricia Anthony,Mitsuru Ishizuka,Dickson Lukose
Publisher : Springer
Page : 905 pages
File Size : 50,9 Mb
Release : 2012-08-27
Category : Computers
ISBN : 9783642326950

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PRICAI 2012: Trends in Artificial Intelligence by Patricia Anthony,Mitsuru Ishizuka,Dickson Lukose Pdf

This volume constitutes the refereed proceedings of the 12th Pacific Rim Conference on Artificial Intelligence, PRICAI 2012, held in Kuching, Malaysia, in September 2012. The 60 revised full papers presented together with 2 invited papers, 22 short papers, and 11 poster papers in this volume were carefully reviewed and selected from 240 submissions. The topics roughly include AI foundations, applications of AI, cognition and intelligent interactions, computer-aided education, constraint and search, creativity support, decision theory, evolutionary computation, game playing, information retrieval and extraction, knowledge mining and acquisition, knowledge representation and logic, linked open data and semantic web, machine learning and data mining, multimedia and AI, natural language processing, robotics, social intelligence, vision and perception, web and text mining, web and knowledge-based system.

Feature Extraction, Construction and Selection

Huan Liu,Hiroshi Motoda

Author : Huan Liu,Hiroshi Motoda
Publisher : Springer Science & Business Media
Page : 418 pages
File Size : 54,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9781461557258

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Feature Extraction, Construction and Selection by Huan Liu,Hiroshi Motoda Pdf

There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data preprocessing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about the research of feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of our endeavor to produce a contemporary overview of modern solutions, to create synergy among these seemingly different branches, and to pave the way for developing meta-systems and novel approaches. Even with today's advanced computer technologies, discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Feature extraction, construction and selection are a set of techniques that transform and simplify data so as to make data mining tasks easier. Feature construction and selection can be viewed as two sides of the representation problem.

Research Companion to Building Information Modeling

Lu, Weisheng,Anumba, Chimay J.

Author : Lu, Weisheng,Anumba, Chimay J.
Publisher : Edward Elgar Publishing
Page : 768 pages
File Size : 41,5 Mb
Release : 2022-03-22
Category : Technology & Engineering
ISBN : 9781839105524

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Research Companion to Building Information Modeling by Lu, Weisheng,Anumba, Chimay J. Pdf

Offering critical insights to the state-of-the-art in Building Information Modeling (BIM) research and development, this book outlines the prospects and challenges for the field in this era of digital revolution. Analysing the contributions of BIM across the construction industry, it provides a comprehensive survey of global BIM practices.

Practical Machine Learning with Python

Dipanjan Sarkar,Raghav Bali,Tushar Sharma

Author : Dipanjan Sarkar,Raghav Bali,Tushar Sharma
Publisher : Apress
Page : 545 pages
File Size : 54,6 Mb
Release : 2017-12-20
Category : Computers
ISBN : 9781484232071

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Practical Machine Learning with Python by Dipanjan Sarkar,Raghav Bali,Tushar Sharma Pdf

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students

Intelligent Music Information Systems: Tools and Methodologies

Shen, Jialie,Shepherd, John,Cui, Bin,Liu, Ling

Author : Shen, Jialie,Shepherd, John,Cui, Bin,Liu, Ling
Publisher : IGI Global
Page : 380 pages
File Size : 52,6 Mb
Release : 2007-08-31
Category : Technology & Engineering
ISBN : 9781599046655

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Intelligent Music Information Systems: Tools and Methodologies by Shen, Jialie,Shepherd, John,Cui, Bin,Liu, Ling Pdf

Modern technology and the development of user-centric applications have grown to encompass many of our everyday routines and interests. Such advances in music data management and information retrieval techniques have crossed the boundaries of expertise from researchers to developers to professionals in the music industry. Intelligent Music Information Systems: Tools and Methodologies provides comprehensive description and analysis into the use of music information retrieval from the data management perspective, and thus provides libraries in academic, commercial, and other settings with a complete reference for multimedia system applications.

31. Forum Bauinformatik

Sternal, Maximilian,Ungureanu, Lucian-Constantin,Böger, Laura,Bindal-Gutsche, Christoph

Author : Sternal, Maximilian,Ungureanu, Lucian-Constantin,Böger, Laura,Bindal-Gutsche, Christoph
Publisher : Universitätsverlag der TU Berlin
Page : 432 pages
File Size : 47,5 Mb
Release : 2019-09-17
Category : Technology & Engineering
ISBN : 9783798331044

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31. Forum Bauinformatik by Sternal, Maximilian,Ungureanu, Lucian-Constantin,Böger, Laura,Bindal-Gutsche, Christoph Pdf

Das Forum Bauinformatik steht unter dem Motto „von jungen Forschenden für junge Forschende“. Es bietet jungen Wissenschaftlerinnen und Wissenschaftlern sowie interessierten Studierenden die Möglichkeit, ihre Forschungsarbeiten zu präsentieren, Problemstellungen fachspezifisch zu diskutieren und sich ganz allgemein über den neusten Stand der Forschung zu informieren. Zudem ergibt sich dadurch eine ausgezeichnete Gelegenheit, in die wissenschaftliche Gemeinschaft im Bereich der Bauinformatik einzusteigen und Kontakte zu anderen Forschenden zu knüpfen. According to the motto “from young researchers for young researchers” the Forum Bauinformatik offers researchers as well as interested undergraduates the opportunity to present their research work, to discuss discipline-specific problems and to catch up to the current state in research. Furthermore, it gives an excellent chance to get in touch with the scientific community in the field of Computing in Civil Engineering and socialize with other researchers

Practical Deep Learning for Cloud, Mobile, and Edge

Anirudh Koul,Siddha Ganju,Meher Kasam

Author : Anirudh Koul,Siddha Ganju,Meher Kasam
Publisher : "O'Reilly Media, Inc."
Page : 585 pages
File Size : 40,6 Mb
Release : 2019-10-14
Category : Computers
ISBN : 9781492034810

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Practical Deep Learning for Cloud, Mobile, and Edge by Anirudh Koul,Siddha Ganju,Meher Kasam Pdf

Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Novel Therapeutic Approaches for Biliary Tract Cancer and Hepatocellular Carcinoma

Daniel Neureiter,Maria Lina Tornesello,Dino Bekric

Author : Daniel Neureiter,Maria Lina Tornesello,Dino Bekric
Publisher : Frontiers Media SA
Page : 138 pages
File Size : 51,7 Mb
Release : 2023-11-24
Category : Science
ISBN : 9782832539668

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Novel Therapeutic Approaches for Biliary Tract Cancer and Hepatocellular Carcinoma by Daniel Neureiter,Maria Lina Tornesello,Dino Bekric Pdf

Hepatobiliary cancers, encompassing biliary tract cancer (BTC) and hepatocellular carcinoma (HCC) are highly lethal. Biliary tract cancer is a deadly disease with a very low five-year survival rate. BTC is assumed to be the fifth most common gastrointestinal malignancy and can be categorized into extrahepatic cholangiocarcinoma (EHC), intrahepatic cholangiocarcinoma (IHC) and gallbladder cancer (GBC), based on the anatomic location. Patients suffering from BTC can be currently treated with radiation therapy, palliative or with a combination of two chemotherapeutics, cisplatin and gemcitabine. Hepatocellular carcinoma is the most prevalent form of liver cancers and was responsible for over 830,000 deaths related to cancer worldwide in 2020. HCC is therefore the second most leading cause of cancer deaths globally. Current treatment options encompass targeted therapy with sorafenib, immunotherapy and post-surgery adjuvant chemotherapy. Factors that might contribute to these dismal outcomes are diagnosis at an already late stage, due to unspecific symptoms, limited therapeutic options, lack of targets and understanding of molecular processes during carcinogenesis as well as resistance to current chemotherapy/treatment. Therefore, these current issues need to be further addressed and solutions and alternative approaches must be provided in order to detect these illnesses at an early stage, prolong the survival time of patients suffering from HCC and BTC and overcome general resistance to available treatment options. The aim of this research topic is to provide an overview about mechanisms of therapy resistance, the identification of therapeutic relevant targets and finally, innovative and alternative approaches for treating BTC and HCC successfully.

Hands-On Machine Learning with ML.NET

Jarred Capellman

Author : Jarred Capellman
Publisher : Packt Publishing Ltd
Page : 287 pages
File Size : 43,7 Mb
Release : 2020-03-27
Category : Computers
ISBN : 9781789804294

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Hands-On Machine Learning with ML.NET by Jarred Capellman Pdf

Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key FeaturesGet well-versed with the ML.NET framework and its components and APIs using practical examplesLearn how to build, train, and evaluate popular machine learning algorithms with ML.NET offeringsExtend your existing machine learning models by integrating with TensorFlow and other librariesBook Description Machine learning (ML) is widely used in many industries such as science, healthcare, and research and its popularity is only growing. In March 2018, Microsoft introduced ML.NET to help .NET enthusiasts in working with ML. With this book, you’ll explore how to build ML.NET applications with the various ML models available using C# code. The book starts by giving you an overview of ML and the types of ML algorithms used, along with covering what ML.NET is and why you need it to build ML apps. You’ll then explore the ML.NET framework, its components, and APIs. The book will serve as a practical guide to helping you build smart apps using the ML.NET library. You’ll gradually become well versed in how to implement ML algorithms such as regression, classification, and clustering with real-world examples and datasets. Each chapter will cover the practical implementation, showing you how to implement ML within .NET applications. You’ll also learn to integrate TensorFlow in ML.NET applications. Later you’ll discover how to store the regression model housing price prediction result to the database and display the real-time predicted results from the database on your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you’ll have learned how to confidently perform basic to advanced-level machine learning tasks in ML.NET. What you will learnUnderstand the framework, components, and APIs of ML.NET using C#Develop regression models using ML.NET for employee attrition and file classificationEvaluate classification models for sentiment prediction of restaurant reviewsWork with clustering models for file type classificationsUse anomaly detection to find anomalies in both network traffic and login historyWork with ASP.NET Core Blazor to create an ML.NET enabled web applicationIntegrate pre-trained TensorFlow and ONNX models in a WPF ML.NET application for image classification and object detectionWho this book is for If you are a .NET developer who wants to implement machine learning models using ML.NET, then this book is for you. This book will also be beneficial for data scientists and machine learning developers who are looking for effective tools to implement various machine learning algorithms. A basic understanding of C# or .NET is mandatory to grasp the concepts covered in this book effectively.

Advances in Building Information Modeling

Salih Ofluoglu,Ozan Onder Ozener,Umit Isikdag

Author : Salih Ofluoglu,Ozan Onder Ozener,Umit Isikdag
Publisher : Springer Nature
Page : 215 pages
File Size : 55,5 Mb
Release : 2020-03-11
Category : Computers
ISBN : 9783030428525

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Advances in Building Information Modeling by Salih Ofluoglu,Ozan Onder Ozener,Umit Isikdag Pdf

This book constitutes the refereed proceedings of the First Eurasian BIM Forum, EBF 2019, held in Istanbul, Turkey, in May 2019. The 16 full papers were carefully reviewed and selected from 44 submissions. The papers cover such topics as BIM adoption and implementation; BIM for project management; BIM for sustainability and performative design; BIM and facility management and infrastructural issues.

Building Intelligent Systems

Geoff Hulten

Author : Geoff Hulten
Publisher : Apress
Page : 346 pages
File Size : 55,5 Mb
Release : 2018-03-06
Category : Computers
ISBN : 9781484234327

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Building Intelligent Systems by Geoff Hulten Pdf

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

Building Feature Extraction With Machine Learning

Building Feature Extraction with Machine Learning by Bharath.H. Aithal,Prakash P.S. Pdf

Remote Sensing Based Building Extraction by Mohammad Awrangjeb,Xiangyun Hu,Bisheng Yang,Jiaojiao Tian Pdf

Machine Learning and Other Artificial Intelligence Applications, An Issue of Neuroimaging Clinics of North America, E-Book by Reza Forghani Pdf

Advances in Noise Reduction and Feature Extraction of Acoustic Signal by Govind Vashishtha,Rajesh Kumar Pdf

PRICAI 2012: Trends in Artificial Intelligence by Patricia Anthony,Mitsuru Ishizuka,Dickson Lukose Pdf

Feature Extraction, Construction and Selection by Huan Liu,Hiroshi Motoda Pdf

Research Companion to Building Information Modeling by Lu, Weisheng,Anumba, Chimay J. Pdf

Practical Machine Learning with Python by Dipanjan Sarkar,Raghav Bali,Tushar Sharma Pdf

Intelligent Music Information Systems: Tools and Methodologies by Shen, Jialie,Shepherd, John,Cui, Bin,Liu, Ling Pdf

31. Forum Bauinformatik by Sternal, Maximilian,Ungureanu, Lucian-Constantin,Böger, Laura,Bindal-Gutsche, Christoph Pdf

Practical Deep Learning for Cloud, Mobile, and Edge by Anirudh Koul,Siddha Ganju,Meher Kasam Pdf

Novel Therapeutic Approaches for Biliary Tract Cancer and Hepatocellular Carcinoma by Daniel Neureiter,Maria Lina Tornesello,Dino Bekric Pdf

Hands-On Machine Learning with ML.NET by Jarred Capellman Pdf

Advances in Building Information Modeling by Salih Ofluoglu,Ozan Onder Ozener,Umit Isikdag Pdf

Building Intelligent Systems by Geoff Hulten Pdf

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