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Title	Architecture Framework For Deep Learning Systems And Iot: An Overview
ID_Doc	10301
Authors	Mehta S.; Mehta J.; Hooda Y.; Singh H.D.
Year	2024
Published	Deep Learning in Internet of Things for Next Generation Healthcare
DOI	http://dx.doi.org/10.1201/9781003451846-2
Abstract	In the rapidly evolving landscape of technology, deep learning (DL) stands out as a transformative subfield of machine learning with the potential to revolutionize knowledge extraction. DL techniques empower us to unearth intricate data representations and hidden insights, promising a future driven by unparalleled performance and accuracy. Concurrently, the Internet of Things (IoT) has emerged as a pivotal force, ushering in an era of interconnected devices that transcend mere buzzwords. From wearable technology to smart cities and industrial ecosystems, the IoT has permeated our lives, promising innovation through data analysis, exploitation, and secure management. IoT architectures, tailored to diverse industries, share foundational attributes of cost-effectiveness, scalability, and functionality. These two technological juggernauts, DL and the IoT, hold the potential to reshape industries and drive innovation, underscoring their transformative power as we navigate the digital frontier. Therefore, this chapter embarks on a comprehensive survey of DL and IoT, delving into their core principles, contemporary methodologies, advantages, drawbacks, architectural paradigms, and applications. © 2024 CRC Press.
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