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Conquer your fear and anxiety learning how the concepts behind object-oriented design apply to the ABAP programming environment. Through simple examples and metaphors this book demystifies the object-oriented programming model. Object-Oriented Design with ABAP presents a bridge from the familiar procedural style of ABAP to the unfamiliar object-oriented style, taking you by the hand and leading you through the difficulties associated with learning these concepts, covering not only the nuances of using object-oriented principles in ABAP software design but also revealing the reasons why these concepts have become embraced throughout the software development industry. More than simply knowing how to use various object-oriented techniques, you'll also be able to determine whether a technique is applicable to the task the software addresses. This book: Shows how object-oriented principles apply to ABAP program design Provides the basics for creating component design diagrams Teaches how to incorporate design patterns in ABAP programs What You’ll Learn: Write ABAP code using the object-oriented model as comfortably and easily as using the procedural model Create ABAP design diagrams based on the Unified Modeling Language Implement object-oriented design patterns into ABAP programs Reap the benefits of spending less time designing and maintaining ABAP programs Recognize those situations where design patterns can be most helpful Avoid long and exhausting searches for the cause of bugs in ABAP programs .

Computer science --- Programming --- Information systems --- Computer. Automation --- object recognition --- computers --- informatica --- programmeertalen --- computerkunde

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Vision is the process of extracting behaviorally-relevant information from patterns of light that fall on retina as the eyes sample the outside world. Traditionally, nonhuman primates (macaque monkeys, in particular) have been viewed by many as the animal model-of-choice for investigating the neuronal substrates of visual processing, not only because their visual systems closely mirror our own, but also because it is often assumed that “simpler” brains lack advanced visual processing machinery. However, this narrow view of visual neuroscience ignores the fact that vision is widely distributed throughout the animal kingdom, enabling a wide repertoire of complex behaviors in species from insects to birds, fish, and mammals. Recent years have seen a resurgence of interest in alternative animal models for vision research, especially rodents. This resurgence is partly due to the availability of increasingly powerful experimental approaches (e.g., optogenetics and two-photon imaging) that are challenging to apply to their full potential in primates. Meanwhile, even more phylogenetically distant species such as birds, fish, and insects have long been workhorse animal models for gaining insight into the core computations underlying visual processing. In many cases, these animal models are valuable precisely because their visual systems are simpler than the primate visual system. Simpler systems are often easier to understand, and studying a diversity of neuronal systems that achieve similar functions can focus attention on those computational principles that are universal and essential. This Research Topic provides a survey of the state of the art in the use of animal models of visual functions that are alternative to macaques. It includes original research, methods articles, reviews, and opinions that exploit a variety of animal models (including rodents, birds, fishes and insects, as well as small New World monkey, the marmoset) to investigate visual function. The experimental approaches covered by these studies range from psychophysics and electrophysiology to histology and genetics, testifying to the richness and depth of visual neuroscience in non-macaque species.

object recognition --- Illusions --- Vision --- rodent --- fish --- Amblyopia --- insect --- Perception --- Visual Cortex --- marmoset

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Vision is the process of extracting behaviorally-relevant information from patterns of light that fall on retina as the eyes sample the outside world. Traditionally, nonhuman primates (macaque monkeys, in particular) have been viewed by many as the animal model-of-choice for investigating the neuronal substrates of visual processing, not only because their visual systems closely mirror our own, but also because it is often assumed that “simpler” brains lack advanced visual processing machinery. However, this narrow view of visual neuroscience ignores the fact that vision is widely distributed throughout the animal kingdom, enabling a wide repertoire of complex behaviors in species from insects to birds, fish, and mammals. Recent years have seen a resurgence of interest in alternative animal models for vision research, especially rodents. This resurgence is partly due to the availability of increasingly powerful experimental approaches (e.g., optogenetics and two-photon imaging) that are challenging to apply to their full potential in primates. Meanwhile, even more phylogenetically distant species such as birds, fish, and insects have long been workhorse animal models for gaining insight into the core computations underlying visual processing. In many cases, these animal models are valuable precisely because their visual systems are simpler than the primate visual system. Simpler systems are often easier to understand, and studying a diversity of neuronal systems that achieve similar functions can focus attention on those computational principles that are universal and essential. This Research Topic provides a survey of the state of the art in the use of animal models of visual functions that are alternative to macaques. It includes original research, methods articles, reviews, and opinions that exploit a variety of animal models (including rodents, birds, fishes and insects, as well as small New World monkey, the marmoset) to investigate visual function. The experimental approaches covered by these studies range from psychophysics and electrophysiology to histology and genetics, testifying to the richness and depth of visual neuroscience in non-macaque species.

object recognition --- Illusions --- Vision --- rodent --- fish --- Amblyopia --- insect --- Perception --- Visual Cortex --- marmoset

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The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.

object recognition --- fMRI --- multimodal data integration --- neural networks --- invariance --- computational neuroscience --- Computer Vision --- Feature representation --- Neurophysiology --- ventral visual pathway

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This monograph by Florian Röhrbein, Germano Veiga and Ciro Natale is an edited collection of 15 authoritative contributions in the area of robot technology transfer between academia and industry. It comprises three parts on Future Industrial Robotics, Robotic Grasping as well as Human-Centered Robots. The book chapters cover almost all the topics nowadays considered ‘hot’ within the robotics community, from reliable object recognition to dexterous grasping, from speech recognition to intuitive robot programming, from mobile robot navigation to aerial robotics, from safe physical human-robot interaction to body extenders. All contributions stem from the results of ECHORD – the European Clearing House for Open Robotics Development, a large-scale integrating project funded by the European Commission within the 7th Framework Programme from 2009 to 2013. ECHORD’s two main pillars were the so-called experiments, 52 small-sized industry-driven research projects, and the structured dialog, a powerful interaction instrument between the stakeholders. The results described in this volume are expected to shed new light on innovation and technology transfer from academia to industry in the field of robotics.  .

Applied physical engineering --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- spraaktechnologie --- object recognition --- automatisering --- KI (kunstmatige intelligentie) --- ingenieurswetenschappen --- robots --- Europe