The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

This book offers a comprehensive study of computer recognition systems – one of the most promising directions in artificial intelligence. It presents a collection of 52 carefully selected articles contributed by experts in the field of pattern recognition, discussing both methodological aspects and applications of current research. It includes the following sections: · Features, learning, and classifiers · Biometrics · Data stream classification and big data analytics · Image processing and computer vision · Medical applications · Applications It is a valuable reference tool for scientists dealing with the problems of designing computer pattern recognition systems, including researchers and students of computer science, artificial intelligence and robotics.

This book presents a collection of high-quality research papers accepted to multi-conference consisting of International Conference on Image Processing and Communications (IP&C 2021), International Conference on Computer Recognition Systems (CORES 2021), International Conference on Advanced Computer Systems (ACS 2021) held jointly in Bydgoszcz, Poland (virtually), in June 2021. The accepted papers address current computer science and computer systems-related technological challenges and solutions, as well as many practical applications and results. The first part of the book deals with advances in pattern recognition and classifiers, the second part is devoted to image processing and computer vision, while the third part addresses practical applications of computer recognition systems. Machine learning solutions for security and networks are tackled in part four of the book, while the last part collects papers on progress in advanced computer systems. We believe this book will be interesting for researchers and practitioners in many fields of computer science and IT applications.

The book covers the latest updates in the application of infrared to biomedical sciences, a non-invasive, contactless, safe and easy approach imaging of skin and tissue temperatures. Its diagnostic procedure allows practitioners to identify the locations of abnormal chemical and blood vessel activity such as angiogenesis in body tissue. Its non-invasive approach works by applying the technology of the infrared camera and state-of-the-art software, where high-resolution digital infrared imaging technology benefits highly from enhanced image production, standardized image interpretation protocols, computerized comparison and storage, and sophisticated image enhancement and analysis. The book contains contributions from global prominent scientists in the area of infrared applications in biomedical studies. The target audience includes academics, practitioners, clinicians and students working in the area of infrared imaging in biomedicine.

The two-volume set LNAI 10841 and LNAI 10842 constitutes the refereed proceedings of the 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, held in Zakopane, Poland in June 2018. The 140 revised full papers presented were carefully reviewed and selected from 242 submissions. The papers included in the second volume are organized in the following five parts: computer vision, image and speech analysis; bioinformatics, biometrics, and medical applications; data mining; artificial intelligence in modeling, simulation and control; and various problems of artificial intelligence.

The two-volume set LNAI 10191 and 10192 constitutes the refereed proceedings of the 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017, held in Kanazawa, Japan, in April 2017. The total of 152 full papers accepted for publication in these proceedings was carefully reviewed and selected from 420 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Intelligent Database Systems; Intelligent Information Systems; Decision Support and Control Systems; Machine Learning and Data Mining; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Intelligent and Context Systems; Multiple Model Approach to Machine Learning; Applications of Data Science; Artificial Intelligence Applications for E-services; Automated Reasoning and Proving Techniques with Applications in Intelligent Systems; Collective Intelligence for Service Innovation, Technology Opportunity, E-Learning and Fuzzy Intelligent Systems; Intelligent Computer Vision Systems and Applications; Intelligent Data Analysis, Applications and Technologies for Internet of Things; Intelligent Algorithms and Brain Functions; Intelligent Systems and Algorithms in Information Sciences; IT in Biomedicine; Intelligent Technologies in the Smart Cities in the 21st Century; Analysis of Image, Video and Motion Data in Life Sciences; Modern Applications of Machine Learning for Actionable Knowledge Extraction; Mathematics of Decision Sciences and Information Science; Scalable Data Analysis in Bioinformatics and Biomedical Informatics; and Technological Perspective of Agile Transformation in IT organizations.

The two-volume set LNCS 12376 and 12377 constitutes the refereed proceedings of the 17th International Conference on Computers Helping People with Special Needs, ICCHP 2020, held in Lecco, Italy, in September 2020. The conference was held virtually due to the COVID-19 pandemic.The 104 papers presented were carefully reviewed and selected from 206 submissions. Included also are 13 introductions. The papers are organized in the following topical sections:Part I: user centred design and user participation in inclusive R&D; artificial intelligence, accessible and assistive technologies; XR accessibility – learning from the past, addressing real user needs and the technical architecture for inclusive immersive environments; serious and fun games; large-scale web accessibility observatories; accessible and inclusive digital publishing; AT and accessibility for blind and low vision users; Art Karshmer lectures in access to mathematics, science and engineering; tactile graphics and models for blind people and recognition of shapes by touch; and environmental sensing technologies for visual impairmentPart II: accessibility of non-verbal communication: making spatial information accessible to people with disabilities; cognitive disabilities and accessibility – pushing the boundaries of inclusion using digital technologies and accessible eLearning environments; ICT to support inclusive education – universal learning design (ULD); hearing systems and accessories for people with hearing loss; mobile health and mobile rehabilitation for people with disabilities: current state, challenges and opportunities; innovation and implementation in the area of independent mobility through digital technologies; how to improve interaction with a text input system; human movement analysis for the design and evaluation of interactive systems and assistive devices; and service and care provision in assistive environments11 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

The proceedings present selected research papers from the CIAC’17, held in Tianjin, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, and etc. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent automation.

This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing methods and algorithm-level solutions, taking also into account those ensemble-learning solutions that embed any of the former alternatives. Furthermore, it focuses on the extension of the problem for multi-class problems, where the former classical methods are no longer to be applied in a straightforward way. This book also focuses on the data intrinsic characteristics that are the main causes which, added to the uneven class distribution, truly hinders the performance of classification algorithms in this scenario. Then, some notes on data reduction are provided in order to understand the advantages related to the use of this type of approaches. Finally this book introduces some novel areas of study that are gathering a deeper attention on the imbalanced data issue. Specifically, it considers the classification of data streams, non-classical classification problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided. This book is highly suitable for technical professionals, senior undergraduate and graduate students in the areas of data science, computer science and engineering. It will also be useful for scientists and researchers to gain insight on the current developments in this area of study, as well as future research directions.

This book constitutes the proceedings of the 15th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2016, held in Vilnius, Lithuania, in September 2016. The 63 regular papers presented together with 1 inivted paper and 5 keynotes in this volume were carefully reviewed and selected from about 89 submissions. The main topics covered are rough set methods for big data analytics; images, visualization, classification; optimization, tuning; scheduling in manufacturing and other applications; algorithms; decisions; intelligent distributed systems; and biometrics, identification, security.