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Alastair Glass Computer Table - Sigrid Mills

International e-Conference on Computer Science (IeCCS 2005)

Fundamentals of Computer Graphics

Probability and Statistics for Computer Scientists

Probability and Statistics for Computer Scientists

Praise for the Second Edition: The author has done his homework on the statistical tools needed for the particular challenges computer scientists encounter. [He] has taken great care to select examples that are interesting and practical for computer scientists. . The content is illustrated with numerous figures and concludes with appendices and an index. The book is erudite and … could work well as a required text for an advanced undergraduate or graduate course. Computing Reviews Probability and Statistics for Computer Scientists Third Edition helps students understand fundamental concepts of Probability and Statistics general methods of stochastic modeling simulation queuing and statistical data analysis; make optimal decisions under uncertainty; model and evaluate computer systems; and prepare for advanced probability-based courses. Written in a lively style with simple language and now including R as well as MATLAB this classroom-tested book can be used for one- or two-semester courses. Features: Axiomatic introduction of probability Expanded coverage of statistical inference and data analysis including estimation and testing Bayesian approach multivariate regression chi-square tests for independence and goodness of fit nonparametric statistics and bootstrap Numerous motivating examples and exercises including computer projects Fully annotated R codes in parallel to MATLAB Applications in computer science software engineering telecommunications and related areas In-Depth yet Accessible Treatment of Computer Science-Related TopicsStarting with the fundamentals of probability the text takes students through topics heavily featured in modern computer science computer engineering software engineering and associated fields such as computer simulations Monte Carlo methods stochastic processes Markov chains queuing theory statistical inference and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). About the Author Michael Baron is David Carroll Professor of Mathematics and Statistics at American University in Washington D. C. He conducts research in sequential analysis and optimal stopping change-point detection Bayesian inference and applications of statistics in epidemiology clinical trials semiconductor manufacturing and other fields. M. Baron is a Fellow of the American Statistical Association and a recipient of the Abraham Wald Prize for the best paper in Sequential Analysis and the Regents Outstanding Teaching Award. M. Baron holds a Ph. D. in statistics from the University of Maryland. In his turn he supervised twelve doctoral students mostly employed on academic and research positions.

GBP 99.99
1

Computer Desk with Drawers and Bookshelf

Computer Aided Policy Making

Computer Desk

Computer Desk

Intelligent Systems and Applications in Computer Vision

Intelligent Systems and Applications in Computer Vision

The book comprehensively covers a wide range of evolutionary computer vision methods and applications feature selection and extraction for training and classification and metaheuristic algorithms in image processing. It further discusses optimized image segmentation its analysis pattern recognition and object detection. Features: Discusses machine learning-based analytics such as GAN networks autoencoders computational imaging and quantum computing Covers deep learning algorithms in computer vision Showcases novel solutions such as multi-resolution analysis in imaging processing and metaheuristic algorithms for tackling challenges associated with image processing Highlight optimization problems such as image segmentation and minimized feature design vector Presents platform and simulation tools for image processing and segmentation The book aims to get the readers familiar with the fundamentals of computational intelligence as well as the recent advancements in related technologies like smart applications of digital images and other enabling technologies from the context of image processing and computer vision. It further covers important topics such as image watermarking steganography morphological processing and optimized image segmentation. It will serve as an ideal reference text for senior undergraduate graduate students and academic researchers in fields including electrical engineering electronics communications engineering and computer engineering. | Intelligent Systems and Applications in Computer Vision

GBP 140.00
1

Applied Computer Vision and Soft Computing with Interpretable AI