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Interpretable Artificial Intelligence: A Perspective of Granular Computing: Studies in Computational Intelligence, cartea 937

Editat de Witold Pedrycz, Shyi-Ming Chen
en Limba Engleză Paperback – 29 mar 2022
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.
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Specificații

ISBN-13: 9783030649517
ISBN-10: 3030649512
Ilustrații: VIII, 429 p. 170 illus., 138 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.61 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.

Textul de pe ultima copertă

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.


Caracteristici

Highlights recent research on interpretable Artificial Intelligence Focuses on a perspective of Granular Computing Written by experts in the field