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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CANON

https://doi.org/10.1007/978-1-4614-9035-7AI is used in every field where AI can be used but with some modification or by adding some techniques of XAI as “SHAP (Shaply Additive exPlanations), DeepSHAP, DeepLIFT, CXplain, and LIME”. The main goal of this chapter is to provide a brief overview of XAI by covering almost every aspect of XAI. T

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https://doi.org/10.1007/978-0-387-85731-2ery difficult to understand. It sometimes becomes a very hard task for the domain experts too to understand the ML algorithms of the black block models, so the need for the development of this type of technology was felt. Many times, results are developed with very high accuracy are quite easy to un

托運

Satellite in Real (Perturbed) Orbit,riteria. The Edge AI community, which spans several ICT, engineering, and perform computer science subfields, researches unique machine learning techniques for the edge computing environment. The objective is to offer a hypothetical roadmap that may unite important players and enablers in order to t

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Michael S. Ritsner,Irving I. Gottesmanstomer service. The best example of explainable edge AI is virtual assistants such as Alexa, google assistant. They learn from the user’s world and phrases and can store them directly on the device. These are just a few examples later, and we have possible applications in future works on the explain

Original

George Foussias,Ofer Agid,Gary Remingtonof parameters, it is difficult to interpret the model creating a black box. The chapter aims to outline the explainability of data fusion at the edge. It highlights different data models of fusion, discusses a framework for AI and data fusion at the edge and identifies potential challenges and possi

AUGER