Proceedings of the Ninth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2017)

Herausgegeben:Abraham, Ajith; Haqiq, Abdelkrim; Muda, Azah Kamilah; Gandhi, Niketa

• Broschiertes Buch

Produktbeschreibung

This book presents 18 carefully selected papers from the ninth edition of the International Conference on Soft Computing and Pattern Recognition (SoCPaR 2017), which was held in Marrakesh, Morocco from December 11 to 13, 2017. A premier conference in the Soft Computing field, SoCPaR brings together the world's leading researchers and practitioners interested in advancing the state of the art in Soft Computing and Pattern Recognition, allowing them to exchange notes on a broad range of disciplines. The book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering.

Produktdetails

• Advances in Intelligent Systems and Computing 737
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-76356-9
• 1st ed. 2018
• Seitenzahl: 212
• Erscheinungstermin: 10. März 2018
• Englisch
• Abmessung: 235mm x 155mm x 12mm
• Gewicht: 344g
• ISBN-13: 9783319763569
• ISBN-10: 3319763563
• Artikelnr.: 50770468

Inhaltsangabe

An Energy-Efficient MAC Protocol for Mobile Wireless Sensor Network Based on IR-UWB.- Obstacle Detection Algorithm by Stereoscopic Image Processing : Navigation Assistance for the Blind and Visually Impaired.- A Simultaneous Topic and Sentiment Classification of Tweets.- Local Directional Multi Radius Binary Pattern: Novel Descriptor for Face Recognition Application.- Content-based Image Retrieval Approach Using Color and Texture Applied to Two Databases (Coil-100 and Wang).- Shape Classification Using B-spline Approximation and Contour Based Shape Descriptors.- An Image Processing Based Framework Using Crowdsourcing for a Successful Suspect Investigation.- Recognition and Classification of Arabic Fricative Consonants.- Cancer Classification Using Gene Expression Profiling: Application of the Filter Approach with the Clustering Algorithm.