| 期刊全稱(chēng) | Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery | | 影響因子2023 | Boris Kovalerchuk,Kawa Nazemi,Ebad Banissi | | 視頻video | http://file.papertrans.cn/163/162337/162337.mp4 | | 發(fā)行地址 | Provides recent research on Artificial Intelligence, Visualization, Visual Knowledge Discovery, and Visual Analytics.Is devoted to AI and Visualization‘for advancing Visual Knowledge Discover.Contains | | 學(xué)科分類(lèi) | Studies in Computational Intelligence | | 圖書(shū)封面 |  | | 影響因子 | .This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields.?Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust.? Such attributes are fundamental to both decision-making and knowledge discovery.? Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form.?? A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts.? Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging.? Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges..This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Vis | | Pindex | Book 2024 |
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