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Interpretable artificial intelligenc...

Pedrycz, Witold.

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Interpretable artificial intelligence = a perspective of granular computing /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Interpretable artificial intelligence/ edited by Witold Pedrycz, Shyi-Ming Chen.
其他題名:	a perspective of granular computing /
其他作者:	Pedrycz, Witold.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	viii, 429 p. :ill. (some col.), digital ;24 cm.
內容註:	Visualizing the Behavior of Convolutional Neural Networks for Time Series Forecasting -- Beyond Deep Event Prediction: Deep Event Understanding based on Explainable Artificial Intelligence -- Interpretation of SVM to build an Explainable AI via Granular Computing -- Factual and Counterfactual Explanation of Fuzzy Information Granules -- Survey of Explainable Machine Learning with Visual and Granular Methods beyond Quasi-explanations -- MiBeX: Malware-inserted Benign Datasets for Explainable Machine Learning -- A Generative Model Based Approach for Zero-shot Breast Cancer Segmentation Explaining Pixels' Contribution to the Model's Prediction.
Contained By:	Springer Nature eBook
標題:	Artificial intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-64949-4
ISBN:	9783030649494

Interpretable artificial intelligence = a perspective of granular computing /
Interpretable artificial intelligencea perspective of granular computing /[electronic resource] :edited by Witold Pedrycz, Shyi-Ming Chen. - Cham :Springer International Publishing :2021. - viii, 429 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.9371860-949X ;. - Studies in computational intelligence ;v.937..

Visualizing the Behavior of Convolutional Neural Networks for Time Series Forecasting -- Beyond Deep Event Prediction: Deep Event Understanding based on Explainable Artificial Intelligence -- Interpretation of SVM to build an Explainable AI via Granular Computing -- Factual and Counterfactual Explanation of Fuzzy Information Granules -- Survey of Explainable Machine Learning with Visual and Granular Methods beyond Quasi-explanations -- MiBeX: Malware-inserted Benign Datasets for Explainable Machine Learning -- A Generative Model Based Approach for Zero-shot Breast Cancer Segmentation Explaining Pixels' Contribution to the Model's Prediction.

This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) - Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.

ISBN: 9783030649494

Standard No.: 10.1007/978-3-030-64949-4doiSubjects--Topical Terms:

516317
Artificial intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Interpretable artificial intelligence = a perspective of granular computing /
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