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The Last Emperor: Constantine XI Paleologus

by Chemdomil Mijatovich ...

Constantine XI Dragases Palaiologos, Latinized as Palaeologus was the last reigningRoman and Byzantine Emperor, ruling as a member of the Palaiologos dynasty from 1449 to his death in battle at the fall of Constantinople in 1453. This is the story of the Last Emperor of the Byzantine Empire, and the Fall of Constantinople to the Ottoman Turks. ... Read more

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Constantine XI Dragases Palaiologos, Latinized as Palaeologus was the last reigningRoman and Byzantine Emperor, ruling as a member of the Palaiologos dynasty from 1449 to his death in battle at the fall of Constantinople in 1453. This is the story of the Last Emperor of the Byzantine Empire, and the Fall of Constantinople to the Ottoman Turks.
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Algorithms on Strings, Trees, and Sequences

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String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book
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Computer Vision for Visual Effects

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Modern blockbuster movies seamlessly introduce impossible characters and action into real-world settings using digital visual effects. These effects are made possible by research from the field of computer vision, the study of how to automatically understand images. Computer Vision for Visual Effects will educate students, engineers and researchers about the fundamental computer vision principles
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Automated Machine Learning

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Edited by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren ...

Series series The Springer Series on Challenges in Machine Learning
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Multimedia Forensics

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Series series Advances in Computer Vision and Pattern Recognition
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Series series Advances in Computer Vision and Pattern Recognition
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This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open
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Introduction to Applied Linear Algebra

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by Stephen Boyd, Lieven Vandenberghe ...

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Series Book 48 - Cambridge Series in Statistical and Probabilistic Mathematics
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Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

by Rudolf Frühwirth, Are Strandlie ...

Series series Particle Acceleration and Detection
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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
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Kernel Methods for Pattern Analysis

by John Shawe-Taylor, Nello Cristianini ...

Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed ... Read more

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Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed
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Building Computer Vision Projects with OpenCV 4 and C++

Implement complex computer vision algorithms and explore deep learning and face detection

by David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot ...

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State Estimation for Robotics

by Timothy D. Barfoot ...

A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents common sensor models and practical advice on how to carry out state estimation for rotations and ... Read more

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A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents common sensor models and practical advice on how to carry out state estimation for rotations and
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Deep Learning

Computer Vision, Python Machine Learning And Neural Networks

by Rob Botwright ...

Introducing the Ultimate AI Book Bundle: Deep Learning, Computer Vision, Python Machine Learning, and Neural NetworksAre you ready to embark on an exhilarating journey into the world of artificial intelligence, deep learning, and computer vision? Look no further! Our carefully curated book bundle, "DEEP LEARNING: COMPUTER VISION, PYTHON MACHINE LEARNING AND NEURAL NETWORKS," offers you a ... Read more

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High-Dimensional Probability

An Introduction with Applications in Data Science

by Roman Vershynin ...

Series Book 47 - Cambridge Series in Statistical and Probabilistic Mathematics
High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate ... Read more

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High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate
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Recommended For You

Optical Data Processing eBooks

The Last Emperor: Constantine XI Paleologus

Algorithms on Strings, Trees, and Sequences

Computer Vision for Visual Effects

Emerging Computing Paradigms

How to Effectively use AI for Beginners

Visualization Analysis and Design

Biomedical Signal and Image Processing

Automated Machine Learning

Understanding Machine Learning

Multimedia Forensics

Experimental Human-Computer Interaction

Cloud-Based Remote Sensing with Google Earth Engine

Cloudera Administration Handbook

Computer Age Statistical Inference

The Little Book of Data

Handbook of Vascular Biometrics

Introduction to Applied Linear Algebra

High-Dimensional Statistics

Pattern Recognition, Tracking and Vertex Reconstruction in Particle Detectors

Kernel Methods for Pattern Analysis

Building Computer Vision Projects with OpenCV 4 and C++

State Estimation for Robotics

Deep Learning

High-Dimensional Probability