BOOKS - Multimodal Intelligent Sensing in Modern Applications
Multimodal Intelligent Sensing in Modern Applications - Masood Ur Rehman, Ahmed Zoha, Muhammad Ali Jamshed, Naeem Ramzan 2025 PDF Wiley-IEEE Press BOOKS
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Multimodal Intelligent Sensing in Modern Applications
Author: Masood Ur Rehman, Ahmed Zoha, Muhammad Ali Jamshed, Naeem Ramzan
Year: 2025
Pages: 307
Format: PDF
File size: 10.1 MB
Language: ENG



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The book "Multimodal Intelligent Sensing in Modern Applications" explores the potential of multimodal sensing technologies to address the challenges of modern society. The book provides an overview of the current state of multimodal sensing research and its applications in various fields such as healthcare, transportation, education, and entertainment. It also discusses the limitations and future directions of this technology. The book begins by examining the concept of multimodal sensing and its importance in modern society. The author explains that multimodal sensing involves the use of multiple sensory modalities, such as vision, speech, gesture, and touch, to capture and interpret human behavior and emotions. This technology has the potential to revolutionize various industries and improve the quality of life for individuals. The book then delves into the various applications of multimodal sensing, including healthcare, where it can be used to monitor patients' vital signs and detect abnormalities, transportation, where it can enhance safety and efficiency, education, where it can provide personalized learning experiences, and entertainment, where it can create immersive gaming and virtual reality experiences. However, the book also acknowledges the limitations of multimodal sensing, such as privacy concerns and ethical issues related to data collection and usage. The author emphasizes the need for a personal paradigm for perceiving the technological process of developing modern knowledge as the basis for the survival of humanity and the survival of the unification of people in a warring state. The book concludes by highlighting the future directions of multimodal sensing research, including the integration of artificial intelligence and machine learning algorithms to improve accuracy and efficiency.
Книга «Мультимодальное интеллектуальное зондирование в современных приложениях» исследует потенциал технологий мультимодального зондирования для решения проблем современного общества. В книге представлен обзор текущего состояния исследований мультимодального зондирования и его применения в различных областях, таких как здравоохранение, транспорт, образование и развлечения. Также обсуждаются ограничения и будущие направления этой технологии. Книга начинается с рассмотрения концепции мультимодального зондирования и его важности в современном обществе. Автор объясняет, что мультимодальное восприятие включает в себя использование нескольких сенсорных модальностей, таких как зрение, речь, жест и прикосновение, для захвата и интерпретации поведения и эмоций человека. Эта технология может революционизировать различные отрасли и улучшить качество жизни людей. Затем в книге рассматриваются различные приложения мультимодального зондирования, включая здравоохранение, где его можно использовать для мониторинга показателей жизнедеятельности пациентов и выявления отклонений от нормы, транспорт, где он может повысить безопасность и эффективность, образование, где он может обеспечить персонализированный опыт обучения, и развлечения, где он может создать захватывающие игровые возможности и возможности виртуальной реальности. Тем не менее, книга также признает ограничения мультимодального зондирования, такие как проблемы конфиденциальности и этические проблемы, связанные со сбором и использованием данных. Автор подчеркивает необходимость личностной парадигмы восприятия технологического процесса развития современного знания как основы выживания человечества и выживания объединения людей в воюющем государстве. В заключение книги освещаются будущие направления исследований мультимодального зондирования, включая интеграцию искусственного интеллекта и алгоритмов машинного обучения для повышения точности и эффективности.
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