Titlebook: Explainable Edge AI: A Futuristic Computing Perspective; Aboul Ella Hassanien,Deepak Gupta,Ankit Garg Book 2023 The Editor(s) (if applicab

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https://doi.org/10.1007/978-0-387-85731-2able to that of humans. But the development of this kind of technology model that mimics humans involves a lot of complex calculations and complex algorithms that are difficult to explain and understand. For this problem, the concept of explainable artificial intelligence (XAI) is developed and intr

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Stanley L. Brodsky,H. O’Neal Smithermanency to AI algorithms so that their predictions can be justified. AI models, their predicted impact, and any biases may all be described using XAI. Human specialists can grasp the forecasts generated by this technology and have trust in the results. Medical AI applications must be transparent in ord

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Michael S. Ritsner,Irving I. Gottesmandevices. Artificial Intelligence algorithms are processed on edge or the devices of users. Edge Computing based on the same premise, stores, processes, and manages data directly at Internet of Things (IoT) endpoints. Edge artificial intelligence uses the device‘s hardware to process data and perform

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Paul H. Lysaker,Molly A. Ericksono become an inherent concern in complex networks as a result of this increase of data. The practise of assessing trust using attributes that influence trust is known as trust evaluation. It is confronted with a number of serious challenges, including a shortage of critical assessment data, a require

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Karen Weston,Mary Ott,Susan Rodger. The sensor nodes are usually characterized as having scarce resources; hence energy efficient mechanisms which can enhance the resource utilization are of great significance. The integration of edge computing framework with the sensor network can aid in the data collection, dissemination and decis

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Studies in Computational Intelligencehttp://image.papertrans.cn/e/image/319296.jpg