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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On the Vulnerability of Deep Reinforcement Learning to Backdoor Attacks in Autonomous Vehicleslearning has shown advanced capabilities in complex tasks and has been applied to autonomous vehicles, e.g., deep neural networks for detection and classification of pedestrians and vehicles, deep reinforcement learning for steering and acceleration control, etc. However, security of autonomous vehi

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Considering the Impact of Noise on Machine Learning Accuracy embedded machine learning (ML). Owing to the consistent improvement in the overall performance of artificial neural networks (ANNs), the reliance of these systems on ANNs as an integral component has seen a constant rise. However, ANNs are known to be considerably vulnerable to noise. This, along w

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Book 2024f?machine learning in embedded, CPS, IoT, and edge computing;?.Offers comprehensive coverage of?hardware design, software design, and hardware/software co-design and co-optimization;?.Describes real applications to?demonstrate how embedded, CPS, IoT, and edge applications benefit from?machine learning..

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Melancholy and Literary Biography, 1640-1816rs due to an error or change in preferences. The ML models must adapt to these changes and provide accurate monitoring. To this end, this chapter reviews the current state of the art and challenges in robust machine learning algorithms for wearable devices. We also perform a case study with a human

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