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5 produkter
5 produkter
E-bok
Engelska, 20113 852 kr
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Machine learning is the branch of artificial intelligence whose goal is to develop algorithms that add learning capabilities to computers. Ensembles are an integral part of machine learning. A typical ensemble includes several algorithms performing the task of prediction of the class label or the degree of class membership for a given input presented as a set of measurable characteristics, often called features. Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.
E-bok
PDF, Engelska, 20183 435 kr
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Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.
E-bok
Engelska, 20183 538 kr
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Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.
3 538 kr
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As technology continues to develop, certain innovations are beginning to cover a wide range of applications, specifically mobile robotic systems. The boundaries between the various automation methods and their implementations are not strictly defined, with overlaps occurring. Specificity is required regarding the research and development of android systems and how they pertain to modern science. Control and Signal Processing Applications for Mobile and Aerial Robotic Systems is a pivotal reference source that provides vital research on the current state of control and signal processing of portable robotic designs. While highlighting topics such as digital systems, control theory, and mathematical methods, this publication explores original inquiry contributions and the instrumentation of mechanical systems in the industrial and scientific fields. This book is ideally designed for technicians, engineers, industry specialists, researchers, academicians, and students seeking current research on today's execution of mobile robotic schemes.
E-bok
PDF, Engelska, 20113 741 kr
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Machine learning is the branch of artificial intelligence whose goal is to develop algorithms that add learning capabilities to computers. Ensembles are an integral part of machine learning. A typical ensemble includes several algorithms performing the task of prediction of the class label or the degree of class membership for a given input presented as a set of measurable characteristics, often called features. Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.