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Computer vision and image analysis play an essential role in 4.0 IR as machine vision and image analysis are indispensable components of every automated environment. Modern machine vision and image analysis techniques play key roles in automation and quality assurance.
This two volume proceedings, LNCS 13445 and 13446, constitutes the refereed proceedings of the 9th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, XR Salento 2022, held in Lecce, Italy, July 6-8, 2022. Due to COVID-19 pandemic the conference was held as a hybrid conference.The 42 full and 16 short papers were carefully reviewed and selected from 84 submissions. The papers discuss key issues, approaches, ideas, open problems, innovative applications and trends in virtual reality, augmented reality, mixed reality, applications in cultural heritage, in medicine, in education, and in industry.
This LNCS 13407 constitutes the refereed proceedings of the 24th International Conference on Information and Communications Security, ICICS 2022, held in Canterbury, UK,, in September 2022. The 34 revised full papers presented in the book were carefully selected from 150 submissionsThe papers are organized around the following topics: Cryptography, Authentication, Privacy and Anonymity, Attacks and Vulnerability Analysis, Artificial Intelligence for Detection, and Network Security and Forensics.
This book constitutes the refereed proceedings of the 12th International Symposium, ISICA 2021, held in Guangzhou, China, during November 19-21, 2021. The 48 full papers included in this book were carefully reviewed and selected from 99 submissions. They were organized in topical sections as follows: new frontier of multi-objective evolutionary algorithms; intelligent multi-media; data modeling and application of artificial intelligence; exploration of novel intelligent optimization algorithm; and intelligent application of industrial production.
This book constitutes the post-conference proceedings of the 23rd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2021, held in Moscow, Russia, in October 2021*.The 16 revised full papers were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections: problem solving infrastructures, experiment organization, and machine learning applications; data analysis in astronomy; data analysis in material and earth sciences; information extraction from text* The conference was held virtually due to the COVID-19 pandemic.
Ultra-High Field Neuro MRI is a comprehensive reference and educational resource on the current state of neuroimaging at ultra-high field (UHF), with an emphasis on 7T. Sections cover the MR physics aspects of UHF, including the technical challenges and practical solutions that have enabled the rapid growth of 7T MRI. Individual chapters are dedicated to the different techniques that most strongly benefit from UHF, as well as chapters with a focus on different application areas in anatomical, functional and metabolic imaging. Finally, several chapters highlight the neurological and psychiatric applications for which 7T has shown benefits. The book is aimed at scientists who develop MR technologies and support clinical and neuroscience research, as well as users who want to benefit from UHF neuro MR techniques in their work. It also provides a comprehensive introduction to the field.
This book constitutes the refereed proceedings of the 6th International Conference on Computer, Communication, and Signal Processing, ICCSP 2022, held in Chennai, India, in February 2022.*The 21 full and 2 short papers presented in this volume were carefully reviewed and selected from 111 submissions. The papers are categorized into topical sub-headings: artificial intelligence and machine learning; Cyber security; and internet of things.*The conference was held as a virtual event due to the COVID-19 pandemic.
This book focuses on seven commonly used image analysis techniques. It covers aspects from basic principles and practical methods, to new advancement of each selected technique to help readers solve image processing related problems in real-life situation.
This book provides a description of designing and developing a computer assisted diagnosis (CAD) system based on thermography for diagnosing some of the common ailments such as arthritis, diabetes, and fever. It introduces applications of machine and deep learning methods, and convolutional neural networks in the development of CAD system.
This book constitutes the refereed proceedings of the 10th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Munich, Germany, in July 2022.The 11 full and poster papers together with 17 short papers included in this volume were carefully reviewed and selected from 32 submitted papers. The papers are organized in the following topical sections: optimization, deep learning architectures, neuroimaging, diffeomorphisms, uncertainty, topology and metrics.
Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases.
How to Optimally Sample and Resample Images: Theory and Methods Using MATLAB provides updated formulations of image sampling theory and practical algorithms of image sampling with sampling rates close to the theoretical minimum, and also introduces interpolation error-free methods of image resampling. Readers will be informed about relevant principles and applications of image sampling with the help of MATLAB(c). The information presented in the book, across 9 chapters, will help readers to understand processes that make analog to digital signal conversion efficient for modern imaging devices.Key Features: - Introduces readers to classical sampling theorems- Presents updated information about image sampling and resampling formulations with reference to theoretical minimums- Presents information on practical and fast sampling algorithms- Presents information about interpolation error-free methods of image resampling- Presents examples of applications of the described methods- Is supplemented by a MATLAB(c) program package for exercising knowledge.The book is a suitable handbook for engineers and technicians involved in imaging engineering and related applications as well as engineering students learning about digital signal processing techniques.
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