Computer vision, image processing, visualisation and computer graphics

This book constitutes the proceedings of the 37th International Conference, IVCNZ 2022, which took place in Auckland, New Zealand, in November 2022. The 37 papers (14 accepted for long oral presentation, 23 for short oral presentation) included in this volume were carefully reviewed and selected from 79 submissions. The conference presents papers on all aspects of computer vision, image processing, computer graphics, virtual and augmented reality, visualization, and HCI applications related to these fields.

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of things (IoT), and information security.

In recent decades, there has been an increasing interest in using machine learning and, in the last few years, deep learning methods combined with other vision and image processing techniques to create systems that solve vision problems in different fields. There is a need for academicians, developers, and industry-related researchers to present, share, and explore traditional and new areas of computer vision, machine learning, deep learning, and their combinations to solve problems. The Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era is designed to serve researchers and developers by sharing original, innovative, and state-of-the-art algorithms and architectures for applications in the areas of computer vision, image processing, biometrics, virtual and augmented reality, and more. It integrates the knowledge of the growing international community of researchers working on the application of machine learning and deep learning methods in vision and robotics. Covering topics such as brain tumor detection, heart disease prediction, and medical image detection, this premier reference source is an exceptional resource for medical professionals, faculty and students of higher education, business leaders and managers, librarians, government officials, researchers, and academicians.

This book constitutes refereed proceedings of the 13th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2021, held in Kallithea, Rhodes, Greece, in October - November 2021. Due to the the COVID-19 pandemic the conference was held online. The 44 full papers and 14 short papers were thoroughly reviewed and selected from 231 submissions. The papers are organized according to the following topical sections: ​​social networks and recommender systems; collective decision-making; computer vision techniques; innovations in intelligent systems; cybersecurity intelligent methods; data mining and machine learning; machine learning in real-world data; Internet of Things and computational technologies for collective intelligence; smart industry and management systems; low resource languages processing; computational intelligence for multimedia understanding.