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Zustand: New. In English.

Zustand: New.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Paperback. Zustand: Brand New. 131 pages. 6.10x0.32x9.25 inches. In Stock.

Zustand: New. In English.

Zustand: New. In English.

Paperback. Zustand: Brand New. 170 pages. 9.18x6.12x9.21 inches. In Stock.

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. Provides a detailed exploration of multimodal learning techniques with a special focus on handling heterogeneous data sourcesDelves into advanced techniques such as deep fusion, graph-based methods, and attention mechanisms, catering to rea.

Hardcover. Zustand: Brand New. 400 pages. 9.18x6.12x9.45 inches. In Stock.

Taschenbuch. Zustand: Neu. Data Science and Security | Proceedings of IDSCS 2025, Volume 1 | Samiksha Shukla (u. a.) | Taschenbuch | Lecture Notes in Networks and Systems | xiii | Englisch | 2026 | Springer | EAN 9783032243591 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the best papers from the International Conference on Data Science for Computational Security (IDSCS 2025), hosted by CHRIST (Deemed to be University), India, and technically sponsored by The Tejas Scientific Researcher Foundation, India, held on November 14 15, 2025. This book covers current research in data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithm design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the best papers from the International Conference on Data Science for Computational Security (IDSCS 2025), organized by CHRIST (Deemed to be University), Bangalore, India, from 14 15 November, 2025. This book targets the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithm design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing. …

Taschenbuch. Zustand: Neu. Neuware - Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.…

Paperback. Zustand: Brand New. 275 pages. 6.14x0.58x9.21 inches. In Stock.

Zustand: New.

Zustand: New.

Zustand: New.