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Visual Computing for Cultural Heritage
This book provides insights into the state of the art of digital cultural heritage using computer graphics, image processing, computer vision, visualization and reconstruction, virtual and augmented reality and serious games. It aims at covering the emergent approaches for digitization and preservation of Cultural Heritage, both in its tangible and intangible facets. Advancements in Digital Cultural Heritage research have been abundant in recent years covering a wide assortment of topics, ranging from visual data acquisition, pre-processing, classification, analysis and synthesis, 3D modelling and reconstruction, semantics and symbolic representation, metadata description, repository and arc...
Transdisciplinary Multispectral Modeling and Cooperation for the Preservation of Cultural Heritage
This two-volume set CCIS 961 and 962 constitutes the refereed post-conference proceedings of the First International Conference on Transdisciplinary Multispectral Modeling and Cooperation for the Preservation of Cultural Heritage, TMM_CH 2018, held in Athens, Greece, in October 2018. 73 revised full papers of 237 submissions are included in these volumes. The papers of the first volume are organized in the following topical sections: the project of the rehabilitation of Holy Sepulchre’s Holy Aedicule as a pilot multispectral, multidimensional, novel approach through transdisciplinary and cooperation in the protection of monuments; digital heritage; novel educational approach for the preser...
Ranking of researchers and scientists in Greece in 2017 according to Google Scholar database
Scope: The classification of researchers and scientists in Greece in a unified list based on the citation impact and dissemination level of their scientific work according to Google Scholar database. Classification criteria: First criterion is h-index. In the case of equal h-index, the following scientometric indicators are used for the classification. The number of total citations, the i10-index, the total impact factor of scientist, the m-index or m-quotient of scientist. Information resource: The h-index, citations and i10-index derived from the public profiles of researchers in the Google Scholar database. In addition, the calculation of total impact factor and m-index of each researcher...
Intelligent Image and Video Analytics
Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover interesting patterns, concepts, relations, and associations. This book includes a review of essential topics and discussion of emerging methods and potential applications of video data mining and analytics. It integrates areas like intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network, and deep learning with focus on multimodality video analytics and recent advances in research/applications...
Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022)
This book summarizes the research findings presented at the 2nd International Conference on Novel & Intelligent Digital Systems (NiDS 2022). NiDS 2022 was implemented virtually due to COVID-19 restrictions, on September 29-30, 2022, under the auspices of the Institute of Intelligent Systems. NiDS lays special emphasis on the novelties of intelligent systems and on the interdisciplinary research which enables, supports, and enhances artificial intelligence (AI) in software development. It promotes high-quality research, creating a forum for the exploration of challenges and new advances in AI, and addresses experts, researchers, and scholars in the fields of artificial and computational intelligence in systems and in computer sciences in general, enabling them to learn more about pertinent, strongly related, and mutually complementary fields. The conference promotes an exchange of ideas, reinforcing and expanding the network of researchers, academics, and market representatives.
MACHINE LEARNING
THE MACHINE LEARNING MCQ (MULTIPLE CHOICE QUESTIONS) SERVES AS A VALUABLE RESOURCE FOR INDIVIDUALS AIMING TO DEEPEN THEIR UNDERSTANDING OF VARIOUS COMPETITIVE EXAMS, CLASS TESTS, QUIZ COMPETITIONS, AND SIMILAR ASSESSMENTS. WITH ITS EXTENSIVE COLLECTION OF MCQS, THIS BOOK EMPOWERS YOU TO ASSESS YOUR GRASP OF THE SUBJECT MATTER AND YOUR PROFICIENCY LEVEL. BY ENGAGING WITH THESE MULTIPLE-CHOICE QUESTIONS, YOU CAN IMPROVE YOUR KNOWLEDGE OF THE SUBJECT, IDENTIFY AREAS FOR IMPROVEMENT, AND LAY A SOLID FOUNDATION. DIVE INTO THE MACHINE LEARNING MCQ TO EXPAND YOUR MACHINE LEARNING KNOWLEDGE AND EXCEL IN QUIZ COMPETITIONS, ACADEMIC STUDIES, OR PROFESSIONAL ENDEAVORS. THE ANSWERS TO THE QUESTIONS ARE PROVIDED AT THE END OF EACH PAGE, MAKING IT EASY FOR PARTICIPANTS TO VERIFY THEIR ANSWERS AND PREPARE EFFECTIVELY.
Advances in Visual Computing
This book constitutes the refereed proceedings of the 14th International Symposium on Visual Computing, ISVC 2019, held in Lake Tahoe, NV, USA in October 2019. The 100 papers presented in this double volume were carefully reviewed and selected from 163 submissions. The papers are organized into the following topical sections: Deep Learning I; Computer Graphics I; Segmentation/Recognition; Video Analysis and Event Recognition; Visualization; ST: Computational Vision, AI and Mathematical methods for Biomedical and Biological Image Analysis; Biometrics; Virtual Reality I; Applications I; ST: Vision for Remote Sensing and Infrastructure Inspection; Computer Graphics II; Applications II; Deep Learning II; Virtual Reality II; Object Recognition/Detection/Categorization; and Poster.
Data Intensive Storage Services for Cloud Environments
With the evolution of digitized data, our society has become dependent on services to extract valuable information and enhance decision making by individuals, businesses, and government in all aspects of life. Therefore, emerging cloud-based infrastructures for storage have been widely thought of as the next generation solution for the reliance on data increases. Data Intensive Storage Services for Cloud Environments provides an overview of the current and potential approaches towards data storage services and its relationship to cloud environments. This reference source brings together research on storage technologies in cloud environments and various disciplines useful for both professionals and researchers.
Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection
This two-volume set LNCS 11196 and LNCS 11197 constitutes the refereed proceedings of the 7th International Conference on Digital Heritage, EuroMed 2018, held in Nicosia, Cyprus, in October/November 2018. The 21 full papers, 47 project papers, and 29 short papers presented were carefully reviewed and selected from 537 submissions. The papers are organized in topical sections on 3D Digitalization, Reconstruction, Modeling, and HBIM; Innovative Technologies in Digital Cultural Heritage; Digital Cultural Heritage –Smart Technologies; The New Era of Museums and Exhibitions; Digital Cultural Heritage Infrastructure; Non Destructive Techniques in Cultural Heritage Conservation; E-Humanities; Reconstructing the Past; Visualization, VR and AR Methods and Applications; Digital Applications for Materials Preservation in Cultural Heritage; and Digital Cultural Heritage Learning and Experiences.
Object Detection with Deep Learning Models
Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks. Features: A structured overview of deep learning in object detection A diversified collection of applications of object detection using deep neural networks Emphasize agriculture and remote sensing domains Exclusive discussion on moving object detection
