Titlebook: Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing; Use Cases and Emergi Sudeep Pasricha,Muhammad Shafique Book 2024 The

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A Survey of Embedded Machine Learning for Smart and Sustainable Healthcare Applicationslows performing machine learning directly on devices used in the field, thus leading to numerous novel applications. Promising target applications include health-related applications such as health monitoring, human activity recognition, human pose estimation, and service applications such as energy management in mobile devices.

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https://doi.org/10.1007/978-3-319-78310-9ne learning algorithms have been proposed that are more accurate as they automatically extract pertinent information from large volumes of data. In this chapter, we explore the recent machine learning algorithms that have been proposed to perform the various tasks within an autonomous system.

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Melanoma Antigens and Antibodiesizes a gated recurrent unit (GRU)-based recurrent autoencoder network to detect cyber-attacks in automotive cyber-physical systems. Our proposed INDRA framework is evaluated under different attacks and compared against various state-of-the-art anomaly detection works using a commercially available vehicular network dataset.

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Machine Learning for Efficient Perception in Automotive Cyber-Physical Systemsesent PASTA, a novel framework for global co-optimization of deep learning and sensing for ADAS-based vehicle perception. Experimental results with the Audi-TT and BMW-Minicooper vehicles show how PASTA can intelligently traverse the perception design space to find robust, vehicle-specific solutions.

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