| 书目名称 | Explainable AI Within the Digital Transformation and Cyber Physical Systems | | 副标题 | XAI Methods and Appl | | 编辑 | Moamar Sayed-Mouchaweh | | 视频video | | | 概述 | Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems.Provides a textual scientific d | | 图书封面 |  | | 描述 | This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefitsand requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions..Includ | | 出版日期 | Book 2021 | | 关键词 | Explainable Artificial Intelligence (XAI); Digital Transformation and Cyber Physical Systems; XAI appl | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-76409-8 | | isbn_softcover | 978-3-030-76411-1 | | isbn_ebook | 978-3-030-76409-8 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
The information of publication is updating
|
|
发表于 2025-3-21 18:47:35
