Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery is popular PDF and ePub book, written by Boris Kovalerchuk in 2022-06-04, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery can be Read Online from any device for your convenience.

Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery Book PDF Summary

This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic. A long-standing challenge of artificial intelligence (AI) and machine learning (ML) is explaining models to humans, especially for live-critical applications like health care. A model explanation is fundamentally human activity, not only an algorithmic one. As current deep learning studies demonstrate, it makes the paradigm based on the visual methods critically important to address this challenge. In general, visual approaches are critical for discovering explainable high-dimensional patterns in all types in high-dimensional data offering "n-D glasses," where preserving high-dimensional data properties and relations in visualizations is a major challenge. The current progress opens a fantastic opportunity in this domain. This book is a collection of 25 extended works of over 70 scholars presented at AI and visual analytics related symposia at the recent International Information Visualization Conferences with the goal of moving this integration to the next level. The sections of this book cover integrated systems, supervised learning, unsupervised learning, optimization, and evaluation of visualizations. The intended audience for this collection includes those developing and using emerging AI/machine learning and visualization methods. Scientists, practitioners, and students can find multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery. The book provides a vision of future directions in this domain. New researchers will find here an inspiration to join the profession and to be involved for further development. Instructors in AI/ML and visualization classes can use it as a supplementary source in their undergraduate and graduate classes.

Detail Book of Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery PDF

Integrating Artificial Intelligence and Visualization for Visual Knowledge Discovery
  • Author : Boris Kovalerchuk
  • Release : 04 June 2022
  • Publisher : Springer Nature
  • ISBN : 9783030931193
  • Genre : Technology & Engineering
  • Total Page : 671 pages
  • Language : English
  • PDF File Size : 16,8 Mb

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Machine Learning and Principles and Practice of Knowledge Discovery in Databases

Machine Learning and Principles and Practice of Knowledge Discovery in Databases Author : Michael Kamp,Irena Koprinska,Adrien Bibal,Tassadit Bouadi,Benoît Frénay,Luis Galárraga,José Oramas,Linara Adilova,Yamuna Krishnamurthy,Bo Kang,Christine Largeron,Jefrey Lijffijt,Tiphaine Viard,Pascal Welke,Massimiliano Ruocco,Erlend Aune,Claudio Gallicchio,Gregor Schiele,Franz Pernkopf,Michaela Blott,Holger Fröning,Günther Schindler,Riccardo Guidotti,Anna Monreale,Salvatore Rinzivillo,Przemyslaw Biecek,Eirini Ntoutsi,Mykola Pechenizkiy,Bodo Rosenhahn,Christopher Buckley,Daniela Cialfi,Pablo Lanillos,Maxwell Ramstead,Tim Verbelen,Pedro M. Ferreira,Giuseppina Andresini,Donato Malerba,Ibéria Medeiros,Philippe Fournier-Viger,M. Saqib Nawaz,Sebastian Ventura,Meng Sun,Min Zhou,Valerio Bitetta,Ilaria Bordino,Andrea Ferretti,Francesco Gullo,Giovanni Ponti,Lorenzo Severini,Rita Ribeiro,João Gama,Ricard Gavaldà,Lee Cooper,Naghmeh Ghazaleh,Jonas Richiardi,Damian Roqueiro,Diego Saldana Miranda,Konstantinos Sechidis,Guilherme Graça
Publisher : Springer Nature
File Size : 28,6 Mb
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