Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python

ISBN-13: 9783030261559 / Angielski / Miękka / 2020 / 406 str.

Joseph Awange; Béla Paláncz; Lajos Völgyesi

Spis treści

Dimension reduction.- Classification.- Clustering.- Regression.- Neural Networks.

O autorze

Professor Joseph Awange joined the Department of Spatial Sciences (Curtin University, Australia) in 2006 under a Curtin Research Fellowship and concurrently undertook the prestigious Alexander von Humboldt (AvH) Fellowship at the Geodetic Institute (Karlsruhe Institute of Technology, Germany) having been awarded the Australian 2008-2011 Ludwig Leichhardt Memorial Fellowship for experienced researchers. In 2015, he won all the three major Fellowship Awards: Alexander von Humboldt (Germany), Japan Society of Promotion of Science (Japan) and Brazil Frontier of Science (Brazil) to carry out research in those countries. At Curtin University, he is currently engaged in teaching and research having attracted more than $1.5M worth of research grants. He obtained his BSc and MSc degrees in Surveying from the University of Nairobi (Kenya), and was also awarded a merit scholarship by the German Academic Exchange Program (DAAD), which facilitated his obtaining a second MSc degree and PhD in Geodesy at Stuttgart University (Germany). In 2002-2004, he was awarded the prestigious Japan Society for Promotion of Science (JSPS) Fellowship to pursue postdoctoral research at Kyoto University (Japan). Prof Awange attained International Editorial role in Springer Earth Science Books and has authored 11 scholarly books with the prestigious Springer publishers and more than 130 peer-reviewed high impact journal publications (in e,g., Remote Sensing of Environment, Journal of Climate, Climatic Change, Advances in Water Resources, International Journal of Climatology, and Journal of Hydrology among others).

Blurb

The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks generalized by up-to-date points of view. Associated algorithms are deposited on iCloud.