- Table View
- List View
Machine Medical Ethics
by Simon Peter van Rysewyk Matthijs PontierThe essays in this book, written by researchers from both humanities and science, describe various theoretical and experimental approaches to adding medical ethics to a machine, what design features are necessary in order to achieve this, philosophical and practical questions concerning justice, rights, decision-making and responsibility in medical contexts, and accurately modeling essential physician-machine-patient relationships. In medical settings, machines are in close proximity with human beings: with patients who are in vulnerable states of health, who have disabilities of various kinds, with the very young or very old and with medical professionals. Machines in these contexts are undertaking important medical tasks that require emotional sensitivity, knowledge of medical codes, human dignity and privacy. As machine technology advances, ethical concerns become more urgent: should medical machines be programmed to follow a code of medical ethics? What theory or theories should constrain medical machine conduct? What design features are required? Should machines share responsibility with humans for the ethical consequences of medical actions? How ought clinical relationships involving machines to be modeled? Is a capacity for empathy and emotion detection necessary? What about consciousness? This collection is the first book that addresses these 21st-century concerns.
Machine Scheduling to Minimize Weighted Completion Times
by Nicoló GusmeroliThis work reviews the most important results regarding the use of the α-point in Scheduling Theory. It provides a number of different LP-relaxations for scheduling problems and seeks to explain their polyhedral consequences. It also explains the concept of the α-point and how the conversion algorithm works, pointing out the relations to the sum of the weighted completion times. Lastly, the book explores the latest techniques used for many scheduling problems with different constraints, such as release dates, precedences, and parallel machines. This reference book is intended for advanced undergraduate and postgraduate students who are interested in scheduling theory. It is also inspiring for researchers wanting to learn about sophisticated techniques and open problems of the field.
Machine Translation
by Deyi Xiong Derek F. WongThis book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.
Machine Translation
by Muyun Yang Shujie LiuThis book constitutes the refereed proceedings of the 12th China Workshop on Machine Translation, CWMT 2016, held in Urumqi, China, in August 2016. The 10 English papers presented in this volume were carefully reviewed and selected from 76 submissions. They deal with statistical machine translation, hybrid machine translation, machine translation evaluation, post editing, alignment, and inducing bilingual knowledge from corpora.
Machine Translation
by Pushpak BhattacharyyaThis book compares and contrasts the principles and practices of rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). Presenting numerous examples, the text introduces language divergence as the fundamental challenge to machine translation, emphasizes and works out word alignment, explores IBM models of machine translation, covers the mathematics of phrase-based SMT, provides complete walk-throughs of the working of interlingua-based and transfer-based RBMT, and analyzes EBMT, showing how translation parts can be extracted and recombined to automatically translate a new input.
Machine Translation (The MIT Press Essential Knowledge series)
by Thierry PoibeauA concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and major players in the industry.The dream of a universal translation device goes back many decades, long before Douglas Adams's fictional Babel fish provided this service in The Hitchhiker's Guide to the Galaxy. Since the advent of computers, research has focused on the design of digital machine translation tools—computer programs capable of automatically translating a text from a source language to a target language. This has become one of the most fundamental tasks of artificial intelligence. This volume in the MIT Press Essential Knowledge series offers a concise, nontechnical overview of the development of machine translation, including the different approaches, evaluation issues, and market potential. The main approaches are presented from a largely historical perspective and in an intuitive manner, allowing the reader to understand the main principles without knowing the mathematical details. The book begins by discussing problems that must be solved during the development of a machine translation system and offering a brief overview of the evolution of the field. It then takes up the history of machine translation in more detail, describing its pre-digital beginnings, rule-based approaches, the 1966 ALPAC (Automatic Language Processing Advisory Committee) report and its consequences, the advent of parallel corpora, the example-based paradigm, the statistical paradigm, the segment-based approach, the introduction of more linguistic knowledge into the systems, and the latest approaches based on deep learning. Finally, it considers evaluation challenges and the commercial status of the field, including activities by such major players as Google and Systran.
Machine Translation and Foreign Language Learning (New Frontiers in Translation Studies)
by Kizito TekwaThe book investigates how machine translation (MT) provides opportunities and increases the willingness to communicate in a foreign language. It is informed by a mixed methods methodological approach that analyzes quantitative and qualitative data of questionnaires and real-time instant messages (IM). The book is unique because it contains tables, figures, and screenshots of actual real-time IM exchanges. It is innovative in discussing IM translation, a novel form of MT, and demonstrates how the technology offers English foreign language learners, in this case, Chinese college students, communication opportunities while increasing their willingness to communicate. The study provides an interesting insight into IM user profiles, clients, and usages. Smartphone screenshots are the locale of the study whose findings have far-reaching implications for students, language and translation instructors, and curriculum designers.
Machine Translation and Translation Theory
by Omri AsscherPervasive and ubiquitous, machine translation systems have been transforming communication and understanding across languages and cultures on a historical scale. Focused on both Neural Machine Translation tools, such as Google Translate, and generative AI tools, such as ChatGPT, Omri Asscher pursues the juncture between machine translation and the diverse, often competing, frameworks of human translation theory. He shines a light on the subtleties of the intersection between the two: the places where machine translation corresponds well with the ideas that have been developed on human translation throughout the years, and the places where machine translation seems to challenge translation theory, and perhaps even require that we rethink some of its basic assumptions.Machine Translation and Translation Theory reflects the need for an accessible, panoramic view on the subject. It offers a detailed discussion of various points of theoretical interest: definitions of translation; equivalence in translation; aesthetics of translation; translation ethics; translation as cross-cultural communication; and translation's historical agency.This is key reading for researchers and students in translation studies, as well as scholars of AI-mediated communication, and computer scientists interested in how machine translation architectures correspond with the understanding of translation in the humanities.
Machine Translation and Transliteration involving Related, Low-resource Languages
by Pushpak Bhattacharyya Anoop KunchukuttanMachine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation. Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.
Machine Translation: 14th China Workshop, Cwmt 2018, Wuyishan, China, October 25-26, 2018, Proceedings (Communications in Computer and Information Science #954)
by Jiajun Chen Jiajun ZhangThis book constitutes the refereed proceedings of the 14th China Workshop on Machine Translation, CWMT 2018, held in Wuyishan, China, in October 2018. The 9 papers presented in this volume were carefully reviewed and selected from 17 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Machine Translation: 15th China Conference, CCMT 2019, Nanchang, China, September 27–29, 2019, Revised Selected Papers (Communications in Computer and Information Science #1104)
by Kevin Knight Shujian HuangThis book constitutes the refereed proceedings of the 15th China Conference on Machine Translation, CCMT 2019, held in Nanchang, China, in September 2019.The 10 full papers presented in this volume were carefully reviewed and selected from 21 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Machine Translation: 16th China Conference, CCMT 2020, Hohhot, China, October 10-12, 2020, Revised Selected Papers (Communications in Computer and Information Science #1328)
by Junhui Li Andy WayThis book constitutes the refereed proceedings of the 16th China Conference on Machine Translation, CCMT 2020, held in Hohhot, China, in October 2020. The 13 papers presented in this volume were carefully reviewed and selected from 78 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Machine Translation: 17th China Conference, CCMT 2021, Xining, China, October 8–10, 2021, Revised Selected Papers (Communications in Computer and Information Science #1464)
by Jinsong Su Rico SennrichThis book constitutes the refereed proceedings of the 17th China Conference on Machine Translation, CCMT 2020, held in Xining, China, in October 2021. The 10 papers presented in this volume were carefully reviewed and selected from 25 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Machine Translation: 18th China Conference, CCMT 2022, Lhasa, China, August 6–10, 2022, Revised Selected Papers (Communications in Computer and Information Science #1671)
by Tong Xiao Juan PinoThis book constitutes the refereed proceedings of the 18th China Conference onMachine Translation, CCMT 2022, held in Lhasa, China, during August 6–10, 2022.The 16 full papers were included in this book were carefully reviewed and selected from 73 submissions.
Machine Translation: 19th China Conference, CCMT 2023, Jinan, China, October 19–21, 2023, Proceedings (Communications in Computer and Information Science #1922)
by Yang Feng Chong FengThis book constitutes the refereed proceedings of the 19th China Conference on Machine Translation, CCMT 2023, held in Jinan, China, during October 19–21, 2023. The 8 full papers and 3 short papers included in this book were carefully reviewed and selected from 71 submissions. They focus on machine translation; improvement of translation models and systems; translation quality estimation; document-level machine translation; low-resource machine translation.
Machine Translation: 20th China Conference, CCMT 2024, Xiamen, China, November 8–10, 2024, Proceedings (Communications in Computer and Information Science #2365)
by Yidong Chen Zhongjun HeThis book constitutes the refereed proceedings of the 20th China Conference on Machine Translation, CCMT 2024, which took place in Xiamen, China, during November 8–10, 2024. The 13 full papers included in this book were carefully reviewed and selected from 52 submissions. They were organized in topical sections as follows: robustness and efficiency of translation models; low-resource machine translation; quality estimation; large language modes for machine translation; multi-modal translation; and machine translation evaluation.
Machine Understanding: Machine Perception and Machine Perception MU (Studies in Computational Intelligence #842)
by Zbigniew Les Magdalena LesThis unique book discusses machine understanding (MU). This new branch of classic machine perception research focuses on perception that leads to understanding and is based on the categories of sensory objects. In this approach the visual and non-visual knowledge, in the form of visual and non-visual concepts, is used in the complex reasoning process that leads to understanding. The book presents selected new concepts, such as perceptual transformations, within the machine understanding framework, and uses perceptual transformations to solve perceptual problems (visual intelligence tests) during understanding, where understanding is regarded as an ability to solve complex visual problems described in the authors’ previous books. Thanks to the uniqueness of the research topics covered, the book appeals to researchers from a wide range of disciplines, especially computer science, cognitive science and philosophy.
Machine Vision Beyond Visible Spectrum
by Riad Hammoud Katsushi Ikeuchi Robert W. Mcmillan Guoliang FanThe material of this book encompasses many disciplines, including visible, infrared, far infrared, millimeter wave, microwave, radar, synthetic aperture radar, and electro-optical sensors as well as the very dynamic topics of image processing, computer vision and pattern recognition. This book is composed of six parts: * Advanced background modeling for surveillance * Advances in Tracking in Infrared imagery * Methods for Pose estimation in Ultrasound and LWIR imagery * Recognition in multi-spectral and synthetic aperture radar * Fusion of disparate sensors * Smart Sensors
Machine Vision Handbook
by Bruce G. BatchelorThe automation of visual inspection is becoming more and more important in modern industry as a consistent, reliable means of judging the quality of raw materials and manufactured goods . The Machine Vision Handbook equips the reader with the practical details required to engineer integrated mechanical-optical-electronic-software systems. Machine vision is first set in the context of basic information on light, natural vision, colour sensing and optics. The physical apparatus required for mechanized image capture - lenses, cameras, scanners and light sources - are discussed followed by detailed treatment of various image-processing methods including an introduction to the QT image processing system. QT is unique to this book, and provides an example of a practical machine vision system along with extensive libraries of useful commands, functions and images which can be implemented by the reader. The main text of the book is completed by studies of a wide variety of applications of machine vision in inspecting and handling different types of object.
Machine Vision Inspection Systems, Machine Learning-Based Approaches
by Prasant Kumar Pattnaik Muthukumaran Malarvel Soumya Ranjan Nayak Surya Narayan PandaMachine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.,), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.
Machine Vision Inspection Systems: Image Processing, Concepts, Methodologies, and Applications
by Prasant Kumar Pattnaik Muthukumaran Malarvel Soumya Ranjan Nayak Surya Narayan Panda Nittaya MuangnakThis edited book brings together leading researchers, academic scientists and research scholars to put forward and share their experiences and research results on all aspects of an inspection system for detection analysis for various machine vision applications. It also provides a premier interdisciplinary platform to present and discuss the most recent innovations, trends, methodology, applications, and concerns as well as practical challenges encountered and solutions adopted in the inspection system in terms of image processing and analytics of machine vision for real and industrial application.Machine vision inspection systems (MVIS) utilized all industrial and non-industrial applications where the execution of their utilities based on the acquisition and processing of images. MVIS can be applicable in industry, governmental, defense, aerospace, remote sensing, medical, and academic/education applications but constraints are different. MVIS entails acceptable accuracy, high reliability, high robustness, and low cost. Image processing is a well-defined transformation between human vision and image digitization, and their techniques are the foremost way to experiment in the MVIS. The digital image technique furnishes improved pictorial information by processing the image data through machine vision perception. Digital image processing has widely been used in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.,), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), barcode reading and traceability, medical diagnosis, weather forecasting, face recognition, defence and space research, etc. This edited book is designed to address various aspects of recent methodologies, concepts and research plan out to the readers for giving more depth insights for perusing research on machine vision using image processing techniques.
Machine Vision and Augmented Intelligence: Select Proceedings of MAI 2022 (Lecture Notes in Electrical Engineering #1007)
by Manish Kumar Bajpai Koushlendra Kumar Singh Akbar Sheikh AkbariThis book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2022). The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the book. The book encompasses all industrial and non-industrial applications. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, image processing, and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in health care, brain-computer interface, cybersecurity, social network analysis, and natural language processing.
Machine Vision and Augmented Intelligence: Select Proceedings of MAI 2023 (Lecture Notes in Electrical Engineering #1211)
by Sangeeta Singh Manish Kumar Bajpai Koushlendra Kumar Singh Subodh SrivastavaThis book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2023). The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the volume. The book theme encompasses all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions based on the capture and processing of images. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, COVID-19, image processing and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in healthcare, brain-computer interface, cybersecurity, and social network analysis, natural language processing, etc.
Machine Vision and Augmented Intelligence—Theory and Applications: Select Proceedings of MAI 2021 (Lecture Notes in Electrical Engineering #796)
by Manish Kumar Bajpai Koushlendra Kumar Singh George GiakosThis book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2021) held at IIIT, Jabalpur, in February 2021. The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the volume. The book theme encompasses all industrial and non-industrial applications in which a combination of hardware and software provides operational guidance to devices in the execution of their functions based on the capture and processing of images. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, COVID-19, image processing and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in healthcare, brain-computer interface, cybersecurity, and social network analysis, natural language processing, etc.
Machine Vision and Industrial Robotics in Manufacturing: Approaches, Technologies, and Applications
by Alex Khang Anuradha Misra Eugenia Litvinova Vugar Abdullayev HajimahmudThis book covers the basics of machine vision and robotics in the manufacturing industry. Major applicability of intelligent machines and robotics in the manufacturing sector are explored in three major areas of product traceability, remote product-monitoring, supply chain, logistics, and product record management. Machine Vision and Industrial Robotics in Manufacturing: Approaches, Technologies, and Applications explains advanced technologies based on Artificial Intelligence and Industrial Internet of Things related to smart manufacturing applications.The book introduces the emerging machines and robotics applications that are enabling smart factories initiatives worldwide. The chapters examine labor productivity, factory device installation, and defective product detection. The authors share modern models, emerging technologies, designs, frameworks, theories, practices, and sustainable approaches to design and implement machine vision with industrial robotics. They also examine the challenging issues associated with the leveraging of technologies related to machine vision, computer vision, robotics, Internet of Things, Industrial Internet of Things technologies, Artificial Intelligence-equipped machines, applications, and automatic techniques for intelligent manufacturing systems and smart factory infrastructure in the era of Industry 4.0 manufacturing. The authors also examine topics such as the role of existing management and production solutions, their limitations, and future directions in manufacturing industry.This book targets a mixed audience of students, engineers, scholars, researchers, academics, and professionals who are learning, researching, and working in the field of machine vision, Artificial Intelligence, Industrial Internet of Things, computer vision, and robotic technologies from different industries and economics.