Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Historiography --- Selectivity (Psychology)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Visual perception. --- Selectivity (Psychology) --- Attention. --- Attention --- Visual perception --- Selectivity (Psychology).

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new 'data world' emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are 'consumed' or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.

Cognitive psychology --- Decision making. --- Cognition. --- Selectivity (Psychology)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Visual attention is a relatively new area of study combining a number of disciplines: artificial neural networks, artificial intelligence, vision science and psychology. The aim is to build computational models similar to human vision in order to solve tough problems for many potential applications including object recognition, unmanned vehicle navigation, and image and video coding and processing. In this book, the authors provide an up to date and highly applied introduction to the topic of visual attention, aiding researchers in creating powerful computer vision systems. Areas covered include the significance of vision research, psychology and computer vision, existing computational visual attention models, and the authors' contributions on visual attention models, and applications in various image and video processing tasks.This book is geared for graduates students and researchers in neural networks, image processing, machine learning, computer vision, and other areas of biologically inspired model building and applications. The book can also be used by practicing engineers looking for techniques involving the application of image coding, video processing, machine vision and brain-like robots to real-world systems. Other students and researchers with interdisciplinary interests will also find this book appealing.. Provides a key knowledge boost to developers of image processing applications. Is unique in emphasizing the practical utility of attention mechanisms. Includes a number of real-world examples that readers can implement in their own work:. robot navigation and object selection. image and video quality assessment. image and video coding. Provides codes for users to apply in practical attentional models and mechanisms.

Computer vision. --- Selectivity (Psychology) --- Computer simulation.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Weed control --- Herbicides --- Pesticide selectivity --- Cereal crops --- Protein plants