How we filter out what is irrelevant so we can focus on what we need to know. We are surrounded by a world rich with visual information, but we pay attention to very little of it, filtering out what is irrelevant so we can focus on what we think we need to know. Advertisers, web designers, and other “attention architects” try hard to get our attention, promoting products with videos on huge outdoor screens, adding flashing banners to websites, and developing computer programs with blinking icons that tempt us to click. Often they succeed in distracting us from what we are supposed to be doing. In How Attention Works, Stefan Van der Stigchel explains the process of attention and what the implications are for our everyday lives. The visual attention system is efficient, Van der Stigchel writes, because it doesn't waste energy processing every scrap of visual data it receives; it gathers only relevant information. We focus on one snippet of information and assume that everything else is stable and consistent with past experience; that's why most people miss even the most glaring continuity errors in films. If an object doesn't meet our expectations, chances are we won't see it. Van der Stigchel makes his case with examples from real life, explaining, among other things, the limitations of color perception (and why fire trucks shouldn't be red); the importance of location (security guards and radiologists, for example, have to know where to look); the attention-getting properties of faces and spiders; what we can learn from someone else's eye movements; why we see what we expect to see (magicians take advantage of this); and visual neglect and unattended information.

This book offers a considered voice on the advertising chaos that colours our rapidly changing media environment in a world of fake news, fast facts and seriously depleted attention stamina. Rather than simply herald disruption, Karen Nelson-Field starts an intelligent conversation on what it will take for businesses to win in an attention economy, the advertising myths we need to leave behind and the scientific evidence we can use to navigate a complex advertising and media ecosystem. This book makes sense of viewability standards, coverage and clutter; it talks about the real quality behind a qCPM and takes a deep dive into the relationship between attention and sales. It explains the stark reality of human attention processing in advertising. Readers will learn how to maximise a viewer’s divided attention by leveraging specific media attributes and using attention-grabbing creative triggers. Nelson-Field asks you to pay attention to a disrupted advertising future without panic, but rather with a keen eye on the things that brand owners can learn to control.

Attention: Theory and Practice provides a balance between a readable overview of attention and an emphasis on how theories and paradigms for the study of attention have developed. The book highlights the important issues and major findings while giving sufficient details of experimental studies, models, and theories so that results and conclusions are easy to follow and evaluate. Rather than brushing over tricky technical details, the authors explain them clearly, giving readers the benefit of understanding the motivation for and techniques of the experiments in order to allow readers to think through results, models, and theories for themselves. Attention is an accessible text for advanced undergraduate and graduate students in psychology, as well as an important resource for researchers and practitioners interested in gaining an overview of the field of attention.

In the past two decades, attention has been one of the most investigated areas of research in perception and cognition. However, the literature on the field contains a bewildering array of findings, and empirical progress has not been matched by consensus on major theoretical issues. The Psychology of Attention presents a systematic review of the main lines of research on attention; the topics range from perception of threshold stimuli to memory storage and decision making. The book develops empirical generalizations about the major issues and suggests possible underlying theoretical principles. Pashler argues that widely assumed notions of processing resources and automaticity are of limited value in understanding human information processing. He proposes a central bottleneck for decision making and memory retrieval, and describes evidence that distinguishes this limitation from perceptual limitations and limited-capacity short-term memory.

From the author of The Productivity Project, a groundbreaking and practical guide to managing your attention--the most powerful resource you have to become more creative, get stuff done, and live a meaningful life. Our attention has never been as overwhelmed as it is today. Many of us recognize that our brains struggle to multitask. Despite this, we feel compelled to fill each moment of our lives to the brim with essential tasks and mindless distraction. Hyperfocus provides profound insights into how you can best take charge of your attention to achieve a greater sense of purpose and productivity throughout the day. The most recent neuroscientific research reveals that the brain has two powerful modes that can be unlocked when we use our attention effectively: a focused mode (hyperfocus), which is the foundation for being highly productive, and a creative mode (scatterfocus), which enables us to connect ideas in novel ways. Hyperfocus helps you access both mental modes so you can concentrate more deeply, think more clearly, and work and live more deliberately every day. Chris Bailey examines topics such as: identifying and dealing with the four key types of distraction and interruption; establishing a clear physical and mental environment in which to work; controlling motivation and working fewer hours to become more productive; taking time-outs with intention; multitasking strategically; and learning when to pay attention and when to let your mind wander wherever it wants to. By transforming how you think about your attention, Hyperfocus reveals that the more effectively you learn to take charge of it, the better you'll be able to manage every aspect of your life.

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem Key FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision problems, NLP, and GANsBook Description In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN models. In this book, you’ll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You’ll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you’ll focus on variational autoencoders and GANs. You’ll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You’ll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you’ll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you’ll understand how to apply deep learning to autonomous vehicles. By the end of this book, you’ll have mastered key deep learning concepts and the different applications of deep learning models in the real world. What you will learnCover advanced and state-of-the-art neural network architecturesUnderstand the theory and math behind neural networksTrain DNNs and apply them to modern deep learning problemsUse CNNs for object detection and image segmentationImplement generative adversarial networks (GANs) and variational autoencoders to generate new imagesSolve natural language processing (NLP) tasks, such as machine translation, using sequence-to-sequence modelsUnderstand DL techniques, such as meta-learning and graph neural networksWho this book is for This book is for data scientists, deep learning engineers and researchers, and AI developers who want to further their knowledge of deep learning and build innovative and unique deep learning projects. Anyone looking to get to grips with advanced use cases and methodologies adopted in the deep learning domain using real-world examples will also find this book useful. Basic understanding of deep learning concepts and working knowledge of the Python programming language is assumed.

Are you tired of feeling overwhelmed and scattered? Do you wish you could maximize your productivity and achieve success effortlessly? In Attention Management, productivity expert Maura Thomas unveils the ultimate guide to increasing your focus and harnessing your attention for peak performance. In this game-changing book, Thomas shares her practical mindfulness techniques to help you regain control over your attention and optimize your productivity. With a clear and systematic approach, she empowers you to effectively prioritize tasks, eliminate distractions, and enhance your ability to concentrate on what truly matters. Whether you're a student, professional, or entrepreneur, this book will equip you with the tools and knowledge to: Conquer information overload and regain mental clarity Cultivate laser-like focus amidst digital distractions Overcome procrastination and stay motivated Reduce stress and increase overall well-being Cultivate a healthy work-life balance Boost creativity and unlock your full potential A must-read business book for anyone seeking to transform their productivity and achieve lasting success!