Download or read book Deep Learning for Multimedia Processing Applications written by Uzair Aslam Bhatti and published by CRC Press. This book was released on 2024-02-21 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos. Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts. Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.

Download or read book Modeling and Using Context written by Michael Beigl and published by Springer. This book was released on 2011-09-25 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2011, held in Karlsruhe, Germany in September 2011. The 17 full papers and 7 short papers presented were carefully reviewed and selected from 54 submissions. In addition the book contains two keynote speeches and 8 poster papers. They cover cutting-edge results from the wide range of disciplines concerned with context, including the cognitive sciences (linguistics, psychology, philosophy, computer science, neuroscience), the social sciences and organization sciences, and all application areas.

Download or read book Recent Advances in Machine Learning Techniques and Sensor Applications for Human Emotion Activity Recognition and Support written by Kyandoghere Kyamakya and published by Springer Nature. This book was released on with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Deep Learning Systems written by Andres Rodriguez and published by Springer Nature. This book was released on 2022-05-31 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads is rapidly growing. Model size, serving latency, and power constraints are a significant challenge in the deployment of DL models for many applications. Therefore, it is imperative to codesign algorithms, compilers, and hardware to accelerate advances in this field with holistic system-level and algorithm solutions that improve performance, power, and efficiency. Advancing DL systems generally involves three types of engineers: (1) data scientists that utilize and develop DL algorithms in partnership with domain experts, such as medical, economic, or climate scientists; (2) hardware designers that develop specialized hardware to accelerate the components in the DL models; and (3) performance and compiler engineers that optimize software to run more efficiently on a given hardware. Hardware engineers should be aware of the characteristics and components of production and academic models likely to be adopted by industry to guide design decisions impacting future hardware. Data scientists should be aware of deployment platform constraints when designing models. Performance engineers should support optimizations across diverse models, libraries, and hardware targets. The purpose of this book is to provide a solid understanding of (1) the design, training, and applications of DL algorithms in industry; (2) the compiler techniques to map deep learning code to hardware targets; and (3) the critical hardware features that accelerate DL systems. This book aims to facilitate co-innovation for the advancement of DL systems. It is written for engineers working in one or more of these areas who seek to understand the entire system stack in order to better collaborate with engineers working in other parts of the system stack. The book details advancements and adoption of DL models in industry, explains the training and deployment process, describes the essential hardware architectural features needed for today's and future models, and details advances in DL compilers to efficiently execute algorithms across various hardware targets. Unique in this book is the holistic exposition of the entire DL system stack, the emphasis on commercial applications, and the practical techniques to design models and accelerate their performance. The author is fortunate to work with hardware, software, data scientist, and research teams across many high-technology companies with hyperscale data centers. These companies employ many of the examples and methods provided throughout the book.

Download or read book Database and Expert Systems Applications written by Christine Strauss and published by Springer Nature. This book was released on 2023-08-15 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set, LNCS 14146 and 14147 constitutes the thoroughly refereed proceedings of the 34th International Conference on Database and Expert Systems Applications, DEXA 2023, held in Penang, Malaysia, in August 2023. The 49 full papers presented together with 35 short papers were carefully reviewed and selected from a total of 155 submissions. The papers are organized in topical sections as follows: Part I: Data modeling; database design; query optimization; knowledge representation; Part II: Rule-based systems; natural language processing; deep learning; neural networks.

Download or read book Frontiers in psychodynamic neuroscience written by Filippo Cieri and published by Frontiers Media SA. This book was released on 2023-04-19 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Era of Interactive Media written by Jesse S. Jin and published by Springer Science & Business Media. This book was released on 2012-08-31 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interactive Media is a new research field and a landmark in multimedia development. The Era of Interactive Media is an edited volume contributed from world experts working in academia, research institutions and industry. The Era of Interactive Media focuses mainly on Interactive Media and its various applications. This book also covers multimedia analysis and retrieval; multimedia security rights and management; multimedia compression and optimization; multimedia communication and networking; and multimedia systems and applications. The Era of Interactive Media is designed for a professional audience composed of practitioners and researchers working in the field of multimedia. Advanced-level students in computer science and electrical engineering will also find this book useful as a secondary text or reference.

Download or read book Computer Vision Imaging and Computer Graphics Theory and Applications written by A. Augusto de Sousa and published by Springer Nature. This book was released on with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computation of Artificial Intelligence and Machine Learning written by Amit Kumar Bairwa and published by Springer Nature. This book was released on with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Resources in Education written by and published by . This book was released on 1998 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Sentiment Analysis in Social Networks written by Federico Alberto Pozzi and published by Morgan Kaufmann. This book was released on 2016-10-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network analysis - Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics - Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies - Provides insights into opinion spamming, reasoning, and social network mining - Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences - Serves as a one-stop reference for the state-of-the-art in social media analytics

Download or read book Cohesion Coherence and Temporal Reference from an Experimental Corpus Pragmatics Perspective written by Cristina Grisot and published by Springer. This book was released on 2018-10-06 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides new methodological and theoretical insights into temporal reference and its linguistic expression, from a cross-linguistic experimental corpus pragmatics approach. Verbal tenses, in general, and more specifically the categories of tense, grammatical and lexical aspect are treated as cohesion ties contributing to the temporal coherence of a discourse, as well as to the cognitive temporal coherence of the mental representations built in the language comprehension process. As such, it investigates the phenomenon of temporal reference at the interface between corpus linguistics, theoretical linguistics and pragmatics, experimental pragmatics, psycholinguistics, natural language processing and machine translation.

Download or read book Advanced Machine Learning written by Dr. Amit Kumar Tyagi and published by BPB Publications. This book was released on 2024-06-29 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Our book is divided into several useful concepts and techniques of machine learning. This book serves as a valuable resource for individuals seeking to deepen their understanding of advanced topics in this field. Learn about various learning algorithms, including supervised, unsupervised, and reinforcement learning, and their mathematical foundations. Discover the significance of feature engineering and selection for enhancing model performance. Understand model evaluation metrics like accuracy, precision, recall, and F1-score, along with techniques like cross-validation and grid search for model selection. Explore ensemble learning methods along with deep learning, unsupervised learning, time series analysis, and reinforcement learning techniques. Lastly, uncover real-world applications of the machine and deep learning algorithms. After reading this book, readers will gain a comprehensive understanding of machine learning fundamentals and advanced techniques. With this knowledge, readers will be equipped to tackle real-world problems, make informed decisions, and develop innovative solutions using machine and deep learning algorithms. KEY FEATURES ● Basic understanding of machine learning algorithms via MATLAB, R, and Python. ● Inclusion of examples related to real-world problems, case studies, and questions related to futuristic technologies. ● Adding futuristic technologies related to machine learning and deep learning. WHAT YOU WILL LEARN ● Ability to tackle complex machine learning problems. ● Understanding of foundations, algorithms, ethical issues, and how to implement each learning algorithm for their own use/ with their data. ● Efficient data analysis for real-time data will be understood by researchers/ students. ● Using data analysis in near future topics and cutting-edge technologies. WHO THIS BOOK IS FOR This book is ideal for students, professors, and researchers. It equips industry experts and academics with the technical know-how and practical implementations of machine learning algorithms. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Statistical Analysis 3. Linear Regression 4. Logistic Regression 5. Decision Trees 6. Random Forest 7. Rule-Based Classifiers 8. Naïve Bayesian Classifier 9. K-Nearest Neighbors Classifiers 10. Support Vector Machine 11. K-Means Clustering 12. Dimensionality Reduction 13. Association Rules Mining and FP Growth 14. Reinforcement Learning 15. Applications of ML Algorithms 16. Applications of Deep Learning 17. Advance Topics and Future Directions

Download or read book Combinatorial Optimization and Applications written by Weili Wu and published by Springer Nature. This book was released on 2024-01-09 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNCS 14461 and LNCS 14462 constitutes the refereed proceedings of the 17th International Conference on Combinatorial Optimization and Applications, COCOA 2023, held in Hawaii, HI, USA, during December 15–17, 2023. The 73 full papers included in the proceedings were carefully reviewed and selected from 117 submissions. They were organized in topical sections as follows: Part I: Optimization in graphs; scheduling; set-related optimization; applied optimization and algorithm; Graph planer and others; Part II: Modeling and algorithms; complexity and approximation; combinatorics and computing; optimization and algorithms; extreme graph and others; machine learning, blockchain and others.

Download or read book Case Conceptualization and Effective Interventions written by Lynn Zubernis and published by SAGE Publications. This book was released on 2015-04-10 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: With fully integrated DSM-5 criteria and current CACREP standards, this text examines case conceptualization and effective treatments across the most common disorders encountered in counseling. The comprehensive approach helps readers develop their professional identities as well as their case conceptualization and intervention skills. Each chapter blends current theory and research with case illustrations and guided practice exercises to anchor the material in real-world application. Using an innovative new Temporal/Contextual (T/C) Model, the book provides an easy-to-apply and practical framework for developing accurate and effective case conceptualizations and treatment plans. Case Conceptualization and Effective Interventions is part of the SAGE Counseling and Professional Identity Series, which targets specific competencies identified by CACREP (Council for Accreditation of Counseling and Related Programs).

Download or read book A Blueprint for Affective Computing written by Klaus R. Scherer and published by Oxford University Press. This book was released on 2010-09-23 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Affective computing' is a branch of computing concerned with the theory and construction of machines which can detect, respond to, and simulate human emotional states. This book presents an interdisciplinary exploration of this rapidly expanding field, aimed at those in psychology, computational neuroscience, computer science, and AI.

Download or read book Music Data Analysis written by Claus Weihs and published by CRC Press. This book was released on 2016-11-17 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.