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Investigations in Pattern Recognition and Computer Vision for Industry 4.0
The approaches to computer vision have undergone a long journey in recent years, but still, innovations are continuing with leverage increases in computing power, new data availability, and new ways to leverage machine-learning algorithms. As a branch of artificial intelligence (AI), computer vision brings meaningful information from images and videos. Such innovations help communicators to run better campaigns, amplify messages further, and stand out in a noisy, crowded marketplace. Investigations in Pattern Recognition and Computer Vision for Industry 4.0 provides a holistic discussion of the new practical applications and use cases of computer vision and communications. Covering topics such as social media filters, mobile computer vision, and AI-powered image editing, this book is ideal for academicians, researchers, postgraduate students, professional data analysts, research and development centers, organizations dealing with healthcare informatics, and IT firms.
Software Usability
This volume delivers a collection of high-quality contributions to help broaden developers’ and non-developers’ minds alike when it comes to considering software usability. It presents novel research and experiences and disseminates new ideas accessible to people who might not be software makers but who are undoubtedly software users.
Speech, Sound and Music Processing: Embracing Research in India
This book constitutes the thoroughly refereed post-proceedings of the 8th International Symposium on Computer Music Modeling and Retrieval, CMMR 2011 and the 20th International Symposium on Frontiers of Research in Speech and Music, FRSM 2011. This year the 2 conferences merged for the first time and were held in Bhubanes, India, in March 2011. The 17 revised full papers presented were specially reviewed and revised for inclusion in this proceedings volume. The book is divided in four main chapters which reflect the high quality of the sessions of CMMR 2011, the collaboration with FRSM 2011 and the Indian influence, in the topics of Indian Music, Music Information Retrieval, Sound analysis synthesis and perception and Speech processing of Indian languages.
Computational Intelligence in Data Mining
This proceeding discuss the latest solutions, scientific findings and methods for solving intriguing problems in the fields of data mining, computational intelligence, big data analytics, and soft computing. This gathers outstanding papers from the fifth International Conference on “Computational Intelligence in Data Mining” (ICCIDM), and offer a “sneak preview” of the strengths and weaknesses of trending applications, together with exciting advances in computational intelligence, data mining, and related fields.
Machine Learning Algorithms Using Scikit and TensorFlow Environments
Machine learning is able to solve real-time problems. It has several algorithms such as classification, clustering, and more. To learn these essential algorithms, we require tools like Scikit and TensorFlow. Machine Learning Algorithms Using Scikit and TensorFlow Environments assists researchers in learning and implementing these critical algorithms. Covering key topics such as classification, artificial neural networks, prediction, random forest, and regression analysis, this premier reference source is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.
Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence
Emotional intelligence has emerged as an important area of research in the artificial intelligence field as it covers a wide range of real-life domains. Though machines may never need all the emotional skills that people need, there is evidence to suggest that machines require at least some of these skills to appear intelligent when interacting with people. To understand how deep learning-based emotional intelligence can be applied and utilized across industries, further study on its opportunities and future directions is required. Multidisciplinary Applications of Deep Learning-Based Artificial Emotional Intelligence explores artificial intelligence applications, such as machine and deep le...
Bio-Inspired Optimization Techniques in Blockchain Systems
In the dynamic landscape of bioinformatics and blockchain technology, a profound challenge is evident: ensuring secure exchange and analysis of complex biological data while maintaining data integrity and ownership. Traditional methods fall short in seamlessly transferring genomic data, spurring the fusion of blockchain innovation and optimization algorithms as a groundbreaking solution. Biology-Inspired Optimization Techniques in Blockchain Systems directly addresses the data integrity and ownership dilemma in bioinformatics and blockchain. Despite the intricacies of genomic data, blockchain's potential solution faces obstacles like data volume and slow transactions. These challenges are adeptly overcome through optimization algorithms. The book, authored by experts in bioinformatics, blockchain, and optimization, offers a comprehensive guide, showcasing how blockchain architecture and biological data intricacies can harmonize. It provides a blueprint for using blockchain to store genomic variants and aligned reads. This work empowers developers, data scientists, and researchers to overcome technological barriers, redefining the landscape of bioinformatics and beyond.
Uncertain Spatiotemporal Data Management for the Semantic Web
In the world of data management, one of the most formidable challenges faced by academic scholars is the effective handling of spatiotemporal data within the semantic web. As our world continues to change dynamically with time, nearly every aspect of our lives, from environmental monitoring to urban planning and beyond, is intrinsically linked to time and space. This synergy has given rise to an avalanche of spatiotemporal data, and the pressing question is how to manage, model, and query this voluminous information effectively. The existing approaches often fall short in addressing the intricacies and uncertainties that come with spatiotemporal data, leaving scholars struggling to unlock it...
Frameworks for Blockchain Standards, Tools, Testbeds, and Platforms
In an era of rapid technological advancements, blockchain technology has emerged as a groundbreaking solution for decentralized trust and immutable record-keeping. Frameworks for Blockchain Standards, Tools, Testbeds, and Platforms delves into the intricate world of blockchain, offering a comprehensive exploration of its various dimensions. At its core, blockchain disrupts the traditional notion of a centralized trusted authority, instead relying on multiple sources of trust and algorithmic consensus for validation. This handbook elucidates the transformative power of blockchain, examining its capacity to offer enduring records that resist modification by trusted or untrusted sources. The co...
