Man-Machine Interactions 5 : 5th International Conference on Man-Machine Interactions, ICMMI 2017 Held at Kraków, Poland, October 3-6, 2017 (Advances in Intelligent Systems and Computing)

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Man-Machine Interactions 5 : 5th International Conference on Man-Machine Interactions, ICMMI 2017 Held at Kraków, Poland, October 3-6, 2017 (Advances in Intelligent Systems and Computing)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 594 p.
  • 商品コード 9783319677910

Full Description

This Proceedings book provides essential insights into the current state of research in the field of human-computer interactions. It presents the outcomes of the International Conference on Man-Machine Interactions (ICMMI 2017), held on October 3-6, 2017, in Cracow, Poland, which offers a unique international platform for researchers and practitioners to share cutting-edge developments related to technologies, algorithms, tools and systems focused on the means by which humans interact and communicate with computers.

This book is the 5th edition in the series and includes a unique selection of high-quality, original papers highlighting the latest theoretical and practical research on technologies, applications and challenges encountered in the rapidly evolving new forms of human-machine relationships. Major research topics covered include human-computer interfaces, bio-data analysis and mining, image analysis and signal processing, decision support and expert systems, pattern recognition, algorithms and optimisations, computer networks, and data management systems. As such, the book offers a valuable resource for researchers in academia, industry and other fields whose work involves man-machine interactions.

Contents

Deep Learning with Dense Random Neural Networks.- Typing Braille Code in the Air with the Leap Motion Controller.- Eye Movement Traits in Differentiating Experts and Laymen.- Improvements in DNA Reads Correction.- Consensus Approach for Detection of Cancer Somatic Mutations.- Hierarchical Agglomerative Clustering of Time-Warped Series.- Early Detection of Fire Hazard using Fuzzy Inference System

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