Applying Machine Vision
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Understanding And Applying Machine Vision Revised And Expanded
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Author : Nello Zeuch
language : en
Publisher: CRC Press
Release Date : 2000-01-03
Understanding And Applying Machine Vision Revised And Expanded written by Nello Zeuch and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-03 with Computers categories.
A discussion of applications of machine vision technology in the semiconductor, electronic, automotive, wood, food, pharmaceutical, printing, and container industries. It describes systems that enable projects to move forward swiftly and efficiently, and focuses on the nuances of the engineering and system integration of machine vision technology.
Applying Machine Vision
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Author : Nello Zuech
language : en
Publisher: Wiley-Interscience
Release Date : 1988
Applying Machine Vision written by Nello Zuech and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
Applying Machine Vision presents a step-by-step analysis to determine the needs for vision systems in manufacturing processes and the necessary characteristics and features a system must have to achieve desired use. It provides the reader with insight about the reality of utilizing vision systems against their promise. Sufficient background is given to enable the reader to make intelligent decisions about system requirements. The present state of vision technology is reviewed briefly.
Understanding And Applying Machine Vision Revised And Expanded
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Author : Nello Zeuch
language : en
Publisher: CRC Press
Release Date : 2000-01-03
Understanding And Applying Machine Vision Revised And Expanded written by Nello Zeuch and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01-03 with Computers categories.
A discussion of applications of machine vision technology in the semiconductor, electronic, automotive, wood, food, pharmaceutical, printing, and container industries. It describes systems that enable projects to move forward swiftly and efficiently, and focuses on the nuances of the engineering and system integration of machine vision technology.
Machine Vision
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Author : Richard K. Miller
language : en
Publisher: Springer Science & Business Media
Release Date : 1989-08-31
Machine Vision written by Richard K. Miller and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-08-31 with Technology & Engineering categories.
Aimed at manufacturing managers and engineers looking for an introduction to computer vision and its potential, this book discusses the areas in which machine vision is being used, explains different types of machine vision hardware and software and summarizes research at several universities.
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods
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Author : Lilhore, Umesh Kumar
language : en
Publisher: IGI Global
Release Date : 2024-03-22
Applying Machine Learning Techniques To Bioinformatics Few Shot And Zero Shot Methods written by Lilhore, Umesh Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.
Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientists’ ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.
Machine Vision For The Inspection Of Natural Products
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Author : Mark Graves
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-18
Machine Vision For The Inspection Of Natural Products written by Mark Graves and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-18 with Technology & Engineering categories.
Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features: - Case studies based on real-world problems to demonstrate the practical application of machine vision systems. - In-depth description of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing. - Systems-level integration of constituent technologies for bespoke applications across a variety of industries. - A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles. Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.
Applying Machine Learning In Science Education Research
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Author : Peter Wulff
language : en
Publisher: Springer Nature
Release Date : 2025-02-28
Applying Machine Learning In Science Education Research written by Peter Wulff and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-28 with Science categories.
This open access textbook offers science education researchers a hands-on guide for learning, critically examining, and integrating machine learning (ML) methods into their science education research projects. These methods power many artificial intelligence (AI)-based technologies and are widely adopted in science education research. ML can expand the methodological toolkit of science education researchers and provide novel opportunities to gain insights on science-related learning and teaching processes, however, applying ML poses novel challenges and is not suitable for every research context. The volume first introduces the theoretical underpinnings of ML methods and their connections to methodological commitments in science education research. It then presents exemplar case studies of ML uses in both formal and informal science education settings. These case studies include open-source data, executable programming code, and explanations of the methodological criteria and commitments guiding ML use in each case. The textbook concludes with a discussion of opportunities and potential future directions for ML in science education. This textbook is a valuable resource for science education lecturers, researchers, under-graduate, graduate and postgraduate students seeking new ways to apply ML in their work.
Applying Machine Learning For Automated Classification Of Biomedical Data In Subject Independent Settings
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Author : Thuy T. Pham
language : en
Publisher: Springer
Release Date : 2018-08-23
Applying Machine Learning For Automated Classification Of Biomedical Data In Subject Independent Settings written by Thuy T. Pham and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-23 with Technology & Engineering categories.
This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three popular saliency criteria for feature selection, showing that they share common limitations, including time-consuming and subjective manual de-facto standard practice, and that existing automated efforts have been predominantly used for subject dependent setting. It then proposes a novel approach for anomaly detection, demonstrating its effectiveness and accuracy for automated classification of biomedical data, and arguing its applicability to a wider range of unsupervised machine learning applications in subject-independent settings.
Computer Vision Accv 98
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Author : Roland Chin
language : en
Publisher: Springer Science & Business Media
Release Date : 1997-12-12
Computer Vision Accv 98 written by Roland Chin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-12-12 with Computers categories.
These two volumes constitute the refereed proceedings of the Third Asian Conference on Computer Vision, ACCV'98, held in Hong Kong, China, in January 1998. The volumes present together a total of 58 revised full papers and 112 revised posters selected from over 300 submissions. The papers are organized in topical sections on biometry, physics-based vision, color vision, robot vision and navigation, OCR and applications, low-level processing, active vision, face and hand posture recognition, segmentation and grouping, computer vision and virtual reality, motion analysis, and object recognition and modeling.
Applied Machine Learning Solutions With Python
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Author : Siddhanta Bhatta
language : en
Publisher: BPB Publications
Release Date : 2021-08-31
Applied Machine Learning Solutions With Python written by Siddhanta Bhatta and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Computers categories.
A problem-focused guide for tackling industrial machine learning issues with methods and frameworks chosen by experts. KEY FEATURES ● Popular techniques for problem formulation, data collection, and data cleaning in machine learning. ● Comprehensive and useful machine learning tools such as MLFlow, Streamlit, and many more. ● Covers numerous machine learning libraries, including Tensorflow, FastAI, Scikit-Learn, Pandas, and Numpy. DESCRIPTION This book discusses how to apply machine learning to real-world problems by utilizing real-world data. In this book, you will investigate data sources, become acquainted with data pipelines, and practice how machine learning works through numerous examples and case studies. The book begins with high-level concepts and implementation (with code!) and progresses towards the real-world of ML systems. It briefly discusses various concepts of Statistics and Linear Algebra. You will learn how to formulate a problem, collect data, build a model, and tune it. You will learn about use cases for data analytics, computer vision, and natural language processing. You will also explore nonlinear architecture, thus enabling you to build models with multiple inputs and outputs. You will get trained on creating a machine learning profile, various machine learning libraries, Statistics, and FAST API. Throughout the book, you will use Python to experiment with machine learning libraries such as Tensorflow, Scikit-learn, Spacy, and FastAI. The book will help train our models on both Kaggle and our datasets. WHAT YOU WILL LEARN ● Construct a machine learning problem, evaluate the feasibility, and gather and clean data. ● Learn to explore data first, select, and train machine learning models. ● Fine-tune the chosen model, deploy, and monitor it in production. ● Discover popular models for data analytics, computer vision, and Natural Language Processing. ● Create a machine learning profile and contribute to the community. WHO THIS BOOK IS FOR This book caters to beginners in machine learning, software engineers, and students who want to gain a good understanding of machine learning concepts and create production-ready ML systems. This book assumes you have a beginner-level understanding of Python. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Problem Formulation in Machine Learning 3. Data Acquisition and Cleaning 4. Exploratory Data Analysis 5. Model Building and Tuning 6. Taking Our Model into Production 7. Data Analytics Use Case 8. Building a Custom Image Classifier from Scratch 9. Building a News Summarization App Using Transformers 10. Multiple Inputs and Multiple Output Models 11. Contributing to the Community 12. Creating Your Project 13. Crash Course in Numpy, Matplotlib, and Pandas 14. Crash Course in Linear Algebra and Statistics 15. Crash Course in FastAPI