Pattern Recognition
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Pattern Recognition
It's only called paranoia if you can't prove it. Cayce is in London to work. Her pathological sensitivity to brands makes her the perfect divining rod for an ad agency that wants to east a new logo. But when she is co-opted into the search for the creator of a strangely addictive on-line film, Cayce wonders if she has done the right - or indeed, safe - thing. And that's before violence, Japanese computer crazies and Russian Mafia men are in the mix. But she wants to discover the source of the film too, and the truth of her father's disappearance in New York, two years ago. And from the way people are trying to stop her, it looks like she's getting close . . .
Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors
This open access book is a comprehensive review of the methods and algorithms that are used in the reconstruction of events recorded by past, running and planned experiments at particle accelerators such as the LHC, SuperKEKB and FAIR. The main topics are pattern recognition for track and vertex finding, solving the equations of motion by analytical or numerical methods, treatment of material effects such as multiple Coulomb scattering and energy loss, and the estimation of track and vertex parameters by statistical algorithms. The material covers both established methods and recent developments in these fields and illustrates them by outlining exemplary solutions developed by selected experiments. The clear presentation enables readers to easily implement the material in a high-level programming language. It also highlights software solutions that are in the public domain whenever possible. It is a valuable resource for PhD students and researchers working on online or offline reconstruction for their experiments.
Pattern Recognition and Machine Learning
This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.