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Book Visual Quality Assessment by Machine Learning

Download or read book Visual Quality Assessment by Machine Learning written by Long Xu and published by Springer. This book was released on 2015-05-09 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book encompasses the state-of-the-art visual quality assessment (VQA) and learning based visual quality assessment (LB-VQA) by providing a comprehensive overview of the existing relevant methods. It delivers the readers the basic knowledge, systematic overview and new development of VQA. It also encompasses the preliminary knowledge of Machine Learning (ML) to VQA tasks and newly developed ML techniques for the purpose. Hence, firstly, it is particularly helpful to the beginner-readers (including research students) to enter into VQA field in general and LB-VQA one in particular. Secondly, new development in VQA and LB-VQA particularly are detailed in this book, which will give peer researchers and engineers new insights in VQA.

Book Image Quality Assessment of Computer generated Images

Download or read book Image Quality Assessment of Computer generated Images written by André Bigand and published by Springer. This book was released on 2018-03-09 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for computer-generated images. This book addresses this problem and presents recent advances based on soft computing. It is aimed at students, practitioners and researchers in the field of image processing and related areas such as computer graphics and visualization. In this book, we first clarify the differences between natural scene images and computer-generated images, and address the problem of Image Quality Assessment (IQA) by focusing on the visual perception of noise. Rather than using known perceptual models, we first investigate the use of soft computing approaches, classically used in Artificial Intelligence, as full-reference and reduced-reference metrics. Thus, by creating Learning Machines, such as SVMs and RVMs, we can assess the perceptual quality of a computer-generated image. We also investigate the use of interval-valued fuzzy sets as a no-reference metric. These approaches are treated both theoretically and practically, for the complete process of IQA. The learning step is performed using a database built from experiments with human users and the resulting models can be used for any image computed with a stochastic rendering algorithm. This can be useful for detecting the visual convergence of the different parts of an image during the rendering process, and thus to optimize the computation. These models can also be extended to other applications that handle complex models, in the fields of signal processing and image processing.

Book Artificial Intelligence and Soft Computing

Download or read book Artificial Intelligence and Soft Computing written by Leszek Rutkowski and published by Springer Nature. This book was released on 2020-10-20 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 12415 and 12416 constitutes the refereed proceedings of of the 19th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2020, held in Zakopane, Poland*, in October 2020. The 112 revised full papers presented were carefully reviewed and selected from 265 submissions. The papers included in the first volume are organized in the following six parts: ​neural networks and their applications; fuzzy systems and their applications; evolutionary algorithms and their applications; pattern classification; bioinformatics, biometrics and medical applications; artificial intelligence in modeling and simulation. The papers included in the second volume are organized in the following four parts: computer vision, image and speech analysis; data mining; various problems of artificial intelligence; agent systems, robotics and control. *The conference was held virtually due to the COVID-19 pandemic.

Book Machine Learning Based Image Quality Assessment Model

Download or read book Machine Learning Based Image Quality Assessment Model written by 陳立恆 and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Medical Image Understanding and Analysis

Download or read book Medical Image Understanding and Analysis written by Bartłomiej W. Papież and published by Springer Nature. This book was released on 2021-07-06 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 25th Conference on Medical Image Understanding and Analysis, MIUA 2021, held in July 2021. Due to COVID-19 pandemic the conference was held virtually. The 32 full papers and 8 short papers presented were carefully reviewed and selected from 77 submissions. They were organized according to following topical sections: biomarker detection; image registration, and reconstruction; image segmentation; generative models, biomedical simulation and modelling; classification; image enhancement, quality assessment, and data privacy; radiomics, predictive models, and quantitative imaging.

Book Visual Signal Quality Assessment

Download or read book Visual Signal Quality Assessment written by Chenwei Deng and published by Springer. This book was released on 2014-11-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of the latest trends/advances in subjective and objective quality evaluation for traditional visual signals, such as 2D images and video, as well as the most recent challenges for the field of multimedia quality assessment and processing, such as mobile video and social media. Readers will learn how to ensure the highest storage/delivery/ transmission quality of visual content (including image, video, graphics, animation, etc.) from the server to the consumer, under resource constraints, such as computation, bandwidth, storage space, battery life, etc.

Book Visual Quality Assessment for Natural and Medical Image

Download or read book Visual Quality Assessment for Natural and Medical Image written by Yong Ding and published by Springer. This book was released on 2018-03-14 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image quality assessment (IQA) is an essential technique in the design of modern, large-scale image and video processing systems. This book introduces and discusses in detail topics related to IQA, including the basic principles of subjective and objective experiments, biological evidence for image quality perception, and recent research developments. In line with recent trends in imaging techniques and to explain the application-specific utilization, it particularly focuses on IQA for stereoscopic (3D) images and medical images, rather than on planar (2D) natural images. In addition, a wealth of vivid, specific figures and formulas help readers deepen their understanding of fundamental and new applications for image quality assessment technology. This book is suitable for researchers, clinicians and engineers as well as students working in related disciplines, including imaging, displaying, image processing, and storage and transmission. By reviewing and presenting the latest advances, and new trends and challenges in the field, it benefits researchers and industrial R&D engineers seeking to implement image quality assessment systems for specific applications or design/optimize image/video processing algorithms.

Book Image Quality Assessment Using an Artificial Neural Network Approach

Download or read book Image Quality Assessment Using an Artificial Neural Network Approach written by Atidel Bouraoui and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Image quality assessment presents a substantial interest for image services that target human observers. Indeed, Image quality can be measured in two different ways. The first, called "subjective quality assessment", is the obvious approach given the subjective nature of the visual data quality. The second one is called "objective quality assessment" that automatically allow to produce values that score image quality. There exists a large array of objective image quality assessment measures for which a taxonomic scheme has been proposed in the beginning of this manuscript. In fact, the first objective of this thesis is to provide a complete and thorough statistical predictive performance assessment of a variety of full-reference objective quality measures over number of subjectively rated image quality databases. The second is to define the image attributes that are the most relevant to its quality evaluation. Two feature selection methods have been used including the structural risk minimization and the neural network based approaches. This allowed us to develop two new objective reduced-reference image quality metrics where the image quality assessment requires the use of only a few features of the reference and the test images. The third objective of this research work is to exploit the supervised machine learning techniques, especially the multilayer perceptron based model, for automatic image quality appreciation. The system learns from the subjective quality scores and builds a model capable to further provide an objective measure that continues to match with the human opinion to any other image. The main target was to optimize the predictive performance of the developed measures according to correlation, monotonicity and accuracy. The default cost function based on error was employed for the first developed measure (that we called ECF) and a customized cost function based on correlation was proposed to design the second metric (that we called CCF). The comparative investigation to eighteen other full-reference image quality algorithms over three image quality databases shows that both ECF and CCF take into consideration the nonlinearities of the human visual system. The ECF is more accurate than the majority of the metrics under study, while the CCF outperforms all its counterparts in terms of correlation and hence monotonicity.

Book Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery

Download or read book Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery written by Boris Kovalerchuk and published by Springer Nature. This book was released on 2022-06-04 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.

Book Machine Learning and Visual Perception

Download or read book Machine Learning and Visual Perception written by Baochang Zhang and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-07-06 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an up-to-date on machine learning and visual perception, including decision tree, Bayesian learning, support vector machine, AdaBoost, object detection, compressive sensing, deep learning, and reinforcement learning. Both classic and novel algorithms are introduced. With abundant practical examples, it is an essential reference to students, lecturers, professionals, and any interested lay readers.

Book Global Trends in Information Systems and Software Applications

Download or read book Global Trends in Information Systems and Software Applications written by P. Venkata Krishna and published by Springer. This book was released on 2012-08-01 with total page 842 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2-Volume-Set, CCIS 0269-CCIS 0270, constitutes the refereed proceedings of the International Conference on Global Trends in Computing and Communication (CCIS 0269) and the International Conference on Global Trends in Information Systems and Software Applications (CCIS 0270), ObCom 2011, held in Vellore, India, in December 2011. The 173 full papers presented together with a keynote paper and invited papers were carefully reviewed and selected from 842 submissions. The conference addresses issues associated with computing, communication and information. Its aim is to increase exponentially the participants' awareness of the current and future direction in the domains and to create a platform between researchers, leading industry developers and end users to interrelate.

Book Pattern Recognition and Machine Intelligence

Download or read book Pattern Recognition and Machine Intelligence written by Ashish Ghosh and published by Springer Nature. This book was released on with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Stereoscopic Image Quality Assessment

Download or read book Stereoscopic Image Quality Assessment written by Yong Ding and published by Springer Nature. This book was released on 2020-10-22 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive review of all aspects relating to visual quality assessment for stereoscopic images, including statistical mathematics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and analyzing the current state-of-the-art in SIQA algorithms, the latest challenges and research directions as well as novel models and paradigms. In addition, a large number of vivid figures and formulas help readers gain a deeper understanding of the foundation and new applications of objective stereoscopic image quality assessment technologies. Reviewing the latest advances, challenges and trends in stereoscopic image quality assessment, this book is a valuable resource for researchers, engineers and graduate students working in related fields, including imaging, displaying and image processing, especially those interested in SIQA research.

Book Image Analysis and Processing   ICIAP 2017

Download or read book Image Analysis and Processing ICIAP 2017 written by Sebastiano Battiato and published by Springer. This book was released on 2017-10-13 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 10484 and 10485 constitutes the refereed proceedings of the 19th International Conference on Image Analysis and Processing, ICIAP 2017, held in Catania, Italy, in September 2017. The 138 papers presented were carefully reviewed and selected from 229 submissions. The papers cover both classic and the most recent trends in image processing, computer vision, and pattern recognition, addressing both theoretical and applicative aspects. They are organized in the following topical sections: video analysis and understanding; pattern recognition and machine learning; multiview geometry and 3D computer vision; image analysis, detection and recognition; multimedia; biomedical and assistive technology; information forensics and security; imaging for cultural heritage and archaeology; and imaging solutions for improving the quality of life.

Book Selective Visual Attention

Download or read book Selective Visual Attention written by Liming Zhang and published by John Wiley & Sons. This book was released on 2013-03-15 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology. The aim is to build computational models similar to human vision in order to solve tough problems for many potential applications including object recognition, unmanned vehicle navigation, and image and video coding and processing. In this book, the authors provide an up to date and highly applied introduction to the topic of visual attention, aiding researchers in creating powerful computer vision systems. Areas covered include the significance of vision research, psychology and computer vision, existing computational visual attention models, and the authors' contributions on visual attention models, and applications in various image and video processing tasks. This book is geared for graduates students and researchers in neural networks, image processing, machine learning, computer vision, and other areas of biologically inspired model building and applications. The book can also be used by practicing engineers looking for techniques involving the application of image coding, video processing, machine vision and brain-like robots to real-world systems. Other students and researchers with interdisciplinary interests will also find this book appealing. Provides a key knowledge boost to developers of image processing applications Is unique in emphasizing the practical utility of attention mechanisms Includes a number of real-world examples that readers can implement in their own work: robot navigation and object selection image and video quality assessment image and video coding Provides codes for users to apply in practical attentional models and mechanisms

Book Pattern Recognition  ICPR International Workshops and Challenges

Download or read book Pattern Recognition ICPR International Workshops and Challenges written by Alberto Del Bimbo and published by Springer Nature. This book was released on 2021-02-20 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 8-volumes set constitutes the refereed of the 25th International Conference on Pattern Recognition Workshops, ICPR 2020, held virtually in Milan, Italy and rescheduled to January 10 - 11, 2021 due to Covid-19 pandemic. The 416 full papers presented in these 8 volumes were carefully reviewed and selected from about 700 submissions. The 46 workshops cover a wide range of areas including machine learning, pattern analysis, healthcare, human behavior, environment, surveillance, forensics and biometrics, robotics and egovision, cultural heritage and document analysis, retrieval, and women at ICPR2020.