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Sequence To Sequence Learning Using Deep Learning For Optical Character Recognition Ocr
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Book Synopsis Machine Learning in Translation by : Peng Wang
Download or read book Machine Learning in Translation written by Peng Wang and published by Taylor & Francis. This book was released on 2023-04-12 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Translation introduces machine learning (ML) theories and technologies that are most relevant to translation processes, approaching the topic from a human perspective and emphasizing that ML and ML-driven technologies are tools for humans. Providing an exploration of the common ground between human and machine learning and of the nature of translation that leverages this new dimension, this book helps linguists, translators, and localizers better find their added value in a ML-driven translation environment. Part One explores how humans and machines approach the problem of translation in their own particular ways, in terms of word embeddings, chunking of larger meaning units, and prediction in translation based upon the broader context. Part Two introduces key tasks, including machine translation, translation quality assessment and quality estimation, and other Natural Language Processing (NLP) tasks in translation. Part Three focuses on the role of data in both human and machine learning processes. It proposes that a translator’s unique value lies in the capability to create, manage, and leverage language data in different ML tasks in the translation process. It outlines new knowledge and skills that need to be incorporated into traditional translation education in the machine learning era. The book concludes with a discussion of human-centered machine learning in translation, stressing the need to empower translators with ML knowledge, through communication with ML users, developers, and programmers, and with opportunities for continuous learning. This accessible guide is designed for current and future users of ML technologies in localization workflows, including students on courses in translation and localization, language technology, and related areas. It supports the professional development of translation practitioners, so that they can fully utilize ML technologies and design their own human-centered ML-driven translation workflows and NLP tasks.
Book Synopsis Emerging Technology Trends in Electronics, Communication and Networking by : Rasika Dhavse
Download or read book Emerging Technology Trends in Electronics, Communication and Networking written by Rasika Dhavse and published by Springer Nature. This book was released on 2022-12-03 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes refereed proceedings of the Fourth International Conference on Emerging Technology Trends in Electronics, Communication and Networking, ET2ECN 2021. The volume covers a wide range of topics, including electronic devices, VLSI design and fabrication, photo electronic systems and applications, integrated optics, embedded systems, wireless communication, optical communication, free-space optics, signal processing, image/audio/video processing, wireless sensor networks, next-generation networks, network security, and many others. The book will serve as a valuable reference resource for academia and researchers across the globe.
Book Synopsis 7th International Conference on Computing, Control and Industrial Engineering (CCIE 2023) by : Yuriy S. Shmaliy
Download or read book 7th International Conference on Computing, Control and Industrial Engineering (CCIE 2023) written by Yuriy S. Shmaliy and published by Springer Nature. This book was released on 2023-07-24 with total page 1060 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2022, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.
Book Synopsis Python Machine Learning by : Dr. Jeevitha Sivasamy
Download or read book Python Machine Learning written by Dr. Jeevitha Sivasamy and published by RK Publication. This book was released on 2024-08-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python Machine Learning is a comprehensive guide to implementing machine learning algorithms using Python. It covers essential concepts in supervised and unsupervised learning, neural networks, and deep learning. With practical examples and step-by-step tutorials, Ideal for both beginners and experienced developers seeking to build, optimize, and deploy machine learning models. It emphasizes hands-on practice, showcasing real-world applications and providing readers with the tools to solve complex problems with Python and popular libraries like scikit-learn, TensorFlow, and Keras.
Book Synopsis Proceedings of International Joint Conference on Computational Intelligence by : Mohammad Shorif Uddin
Download or read book Proceedings of International Joint Conference on Computational Intelligence written by Mohammad Shorif Uddin and published by Springer Nature. This book was released on 2020-05-22 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2019), held at the University of Liberal Arts Bangladesh (ULAB), Dhaka, on 25–26 October 2019 and jointly organized by the University of Liberal Arts Bangladesh (ULAB), Bangladesh; Jahangirnagar University (JU), Bangladesh; and South Asian University (SAU), India. These proceedings present novel contributions in the areas of computational intelligence, and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.
Book Synopsis Document Analysis and Recognition – ICDAR 2021 by : Josep Lladós
Download or read book Document Analysis and Recognition – ICDAR 2021 written by Josep Lladós and published by Springer Nature. This book was released on 2021-09-03 with total page 758 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports. The papers are organized into the following topical sections: extracting document semantics, text and symbol recognition, document analysis systems, office automation, signature verification, document forensics and provenance analysis, pen-based document analysis, human document interaction, document synthesis, and graphs recognition.
Book Synopsis Deep Learning with Azure by : Mathew Salvaris
Download or read book Deep Learning with Azure written by Mathew Salvaris and published by Apress. This book was released on 2018-08-24 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.
Book Synopsis Machine Learning Infrastructure and Best Practices for Software Engineers by : Miroslaw Staron
Download or read book Machine Learning Infrastructure and Best Practices for Software Engineers written by Miroslaw Staron and published by Packt Publishing Ltd. This book was released on 2024-01-31 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficiently transform your initial designs into big systems by learning the foundations of infrastructure, algorithms, and ethical considerations for modern software products Key Features Learn how to scale-up your machine learning software to a professional level Secure the quality of your machine learning pipeline at runtime Apply your knowledge to natural languages, programming languages, and images Book DescriptionAlthough creating a machine learning pipeline or developing a working prototype of a software system from that pipeline is easy and straightforward nowadays, the journey toward a professional software system is still extensive. This book will help you get to grips with various best practices and recipes that will help software engineers transform prototype pipelines into complete software products. The book begins by introducing the main concepts of professional software systems that leverage machine learning at their core. As you progress, you’ll explore the differences between traditional, non-ML software, and machine learning software. The initial best practices will guide you in determining the type of software you need for your product. Subsequently, you will delve into algorithms, covering their selection, development, and testing before exploring the intricacies of the infrastructure for machine learning systems by defining best practices for identifying the right data source and ensuring its quality. Towards the end, you’ll address the most challenging aspect of large-scale machine learning systems – ethics. By exploring and defining best practices for assessing ethical risks and strategies for mitigation, you will conclude the book where it all began – large-scale machine learning software.What you will learn Identify what the machine learning software best suits your needs Work with scalable machine learning pipelines Scale up pipelines from prototypes to fully fledged software Choose suitable data sources and processing methods for your product Differentiate raw data from complex processing, noting their advantages Track and mitigate important ethical risks in machine learning software Work with testing and validation for machine learning systems Who this book is for If you’re a machine learning engineer, this book will help you design more robust software, and understand which scaling-up challenges you need to address and why. Software engineers will benefit from best practices that will make your products robust, reliable, and innovative. Decision makers will also find lots of useful information in this book, including guidance on what to look for in a well-designed machine learning software product.
Book Synopsis Frontiers in Handwriting Recognition by : Utkarsh Porwal
Download or read book Frontiers in Handwriting Recognition written by Utkarsh Porwal and published by Springer Nature. This book was released on 2022-11-25 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 18th International Conference on Frontiers in Handwriting Recognition, ICFHR 2022, which took place in Hyderabad, India, during December 4-7, 2022. The 36 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 61 submissions. The contributions were organized in topical sections as follows: Historical Document Processing; Signature Verification and Writer Identification; Symbol and Graphics Recognition; Handwriting Recognition and Understanding; Handwriting Datasets and Synthetic Handwriting Generation; Document Analysis and Processing.
Book Synopsis Computer Vision – ECCV 2022 by : Shai Avidan
Download or read book Computer Vision – ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-10-20 with total page 806 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Book Synopsis Decision Intelligence Analytics and the Implementation of Strategic Business Management by : P. Mary Jeyanthi
Download or read book Decision Intelligence Analytics and the Implementation of Strategic Business Management written by P. Mary Jeyanthi and published by Springer Nature. This book was released on 2022-01-01 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.
Book Synopsis Natural Language Processing and Chinese Computing by : Wei Lu
Download or read book Natural Language Processing and Chinese Computing written by Wei Lu and published by Springer Nature. This book was released on 2022-09-23 with total page 878 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of LNAI 13551 and 13552 constitutes the refereed proceedings of the 11th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2022, held in Guilin, China, in September 2022. The 62 full papers, 21 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 327 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability.
Book Synopsis Explanation Based Learning by : Fouad Sabry
Download or read book Explanation Based Learning written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-30 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Explanation Based Learning A type of machine learning known as explanation-based learning, or EBL for short, takes advantage of an extremely robust, or even flawless, domain theory in order to generalize from training data or construct concepts. It also has a connection with encoding, or memory, which assists with learning. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Explanation-based learning Chapter 2: Computational linguistics Chapter 3: Natural language processing Chapter 4: Corpus linguistics Chapter 5: Parsing Chapter 6: Question answering Chapter 7: Link grammar Chapter 8: Grammar induction Chapter 9: Structured prediction Chapter 10: Deep linguistic processing (II) Answering the public top questions about explanation based learning. (III) Real world examples for the usage of explanation based learning in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of explanation based learning' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of explanation based learning.
Book Synopsis Document Analysis and Recognition – ICDAR 2024 Workshops by : Harold Mouchère
Download or read book Document Analysis and Recognition – ICDAR 2024 Workshops written by Harold Mouchère and published by Springer Nature. This book was released on with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optical Character Recognition Systems for Different Languages with Soft Computing by : Arindam Chaudhuri
Download or read book Optical Character Recognition Systems for Different Languages with Soft Computing written by Arindam Chaudhuri and published by Springer. This book was released on 2016-12-23 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.
Book Synopsis Getting started with Deep Learning for Natural Language Processing by : Sunil Patel
Download or read book Getting started with Deep Learning for Natural Language Processing written by Sunil Patel and published by BPB Publications. This book was released on 2021-01-13 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to redesign NLP applications from scratch. KEY FEATURESÊÊ ¥ Get familiar with the basics of any Machine Learning or Deep Learning application. ¥ Understand how does preprocessing work in NLP pipeline. ¥ Use simple PyTorch snippets to create basic building blocks of the network commonly used inÊ NLP.Ê ¥ Learn how to build a complex NLP application. ¥ Get familiar with the advanced embedding technique, Generative network, and Audio signal processing techniques. ÊÊ DESCRIPTIONÊ Natural language processing (NLP) is one of the areas where many Machine Learning and Deep Learning techniques are applied. This book covers wide areas, including the fundamentals of Machine Learning, Understanding and optimizing Hyperparameters, Convolution Neural Networks (CNN), and Recurrent Neural Networks (RNN). This book not only covers the classical concept of text processing but also shares the recent advancements. This book will empower users in designing networks with the least computational and time complexity. This book not only covers basics of Natural Language Processing but also helps in deciphering the logic behind advanced concepts/architecture such as Batch Normalization, Position Embedding, DenseNet, Attention Mechanism, Highway Networks, Transformer models and Siamese Networks. This book also covers recent advancements such as ELMo-BiLM, SkipThought, and Bert. This book also covers practical implementation with step by step explanation of deep learning techniques in Topic Modelling, Text Generation, Named Entity Recognition, Text Summarization, and Language Translation. In addition to this, very advanced and open to research topics such as Generative Adversarial Network and Speech Processing are also covered. WHAT YOU WILL LEARNÊ ¥ Learn how to leveraging GPU for Deep Learning ¥ Learn how to use complex embedding models such as BERT ¥ Get familiar with the common NLP applications. ¥ Learn how to use GANs in NLP ¥ Learn how to process Speech data and implementing it in Speech applications Ê WHO THIS BOOK IS FORÊ This book is a must-read to everyone who wishes to start the career with Machine learning and Deep Learning. This book is also for those who want to use GPU for developing Deep Learning applications. TABLE OF CONTENTSÊÊ 1. Understanding the basics of learning Process 2. Text Processing Techniques 3. Representing Language Mathematically 4. Using RNN for NLP 5. Applying CNN In NLP Tasks 6. Accelerating NLP with Advanced Embeddings 7. Applying Deep Learning to NLP tasks 8. Application of Complex Architectures in NLP 9. Understanding Generative Networks 10. Techniques of Speech Processing 11. The Road Ahead
Book Synopsis Innovations in Computer Science and Engineering by : H. S. Saini
Download or read book Innovations in Computer Science and Engineering written by H. S. Saini and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features a collection of high-quality, peer-reviewed research papers presented at the 8th International Conference on Innovations in Computer Science & Engineering (ICICSE 2020), held at Guru Nanak Institutions, Hyderabad, India, on 28-29 August 2020. It covers the latest research in data science and analytics, cloud computing, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks and IoT applications, artificial intelligence, expert systems, natural language processing, image processing, computer vision and artificial neural networks. .
