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The Leopard in the Pool
The tidal wave of transformation has taken a hold of humanity. Never before in history have humans been overwhelmed by the tsunami of information presented by electronics of all kinds. We are now immersed in the super cyber highway of information and surrounded by the spider web of communications spanning the depths of the oceans to synchronized satellite constellations in space. We now exist in a virtual world where our neural network is wired like never before; people communicate via their computers or text rather than talk face-to-face, relationships evolve online, creativity and breakthrough innovation is stifled where holding a thought is a fleeting fancy replaced with the insatiable em...
Marketing Management
Marketing Management book explains the basic fundamentals of marketing...
Deep Learning and Data Labeling for Medical Applications
This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.
Why Do Indians . . . ?
The world relishes beef. Indians ban it. The world thinks cricket is just a game. For Indians, it is a religion. The world cant comprehend arranged marriage. For Indians, it is still a way of life. Ever wondered why? While interacting with curious non-Indian friends, I had to ponder about it. And the result is five honest humorous semifictional stories that you can relate to.
Disaster Risk Reduction for Economic Growth and Livelihood
The prevalence of natural disasters in recent years has highlighted the importance of preparing adequately for disasters and dealing efficiently with their consequences. This book addresses how countries can enhance their resilience against natural disasters and move towards economic growth and sustainable development. Covering a wide range of issues, it shows how well thought-out measures can be applied to minimize the impacts of disasters in a variety of situations. Starting with the need for coping with a rapidly changing global environment, the book goes on to demonstrate ways to strengthen awareness of the effectiveness of preventive measures, including in the reconstruction phase. The ...
Data Driven: Harnessing Data and AI to Reinvent Customer Engagement
Axiom Business Book Award Silver Medalist in Business TechnologyThe indispensable guide to data-powered marketing from the team behind the data management platform that helps fuel Salesforce―the #1 customer relationship management (CRM) company in the worldA tectonic shift in the practice of marketing is underway. Digital technology, social media, and e-commerce have radically changed the way consumers access information, order products, and shop for services. Using the latest technologies―cloud, mobile, social, internet of things (IoT), and artificial intelligence (AI)―we have more data about consumers and their needs, wants, and affinities than ever before. Data Driven will show you ...
AI in the Wild
Examining the potential benefits and risks of using artificial intelligence to advance global sustainability. Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, explo...
Child Data Citizen
An examination of the datafication of family life--in particular, the construction of our children into data subjects. Our families are being turned into data, as the digital traces we leave are shared, sold, and commodified. Children are datafied even before birth, with pregnancy apps and social media postings, and then tracked through babyhood with learning apps, smart home devices, and medical records. If we want to understand the emergence of the datafied citizen, Veronica Barassi argues, we should look at the first generation of datafied natives: our children. In Child Data Citizen, she examines the construction of children into data subjects, describing how their personal information is collected, archived, sold, and aggregated into unique profiles that can follow them across a lifetime.
Autonorama
“The foundation has been laid for fully autonomous,” Elon Musk announced in 2016, when he assured the world that Tesla would have a driverless fleet on the road in 2017. “It’s twice as safe as a human, maybe better.” Promises of technofuturistic driving utopias have been ubiquitous wherever tech companies and carmakers meet. In Autonorama: The Illusory Promise of High-Tech Driving, technology historian Peter Norton argues that driverless cars cannot be the safe, sustainable, and inclusive “mobility solutions” that tech companies and automakers are promising us. The salesmanship behind the driverless future is distracting us from investing in better ways to get around that we ca...
Computational, label, and data efficiency in deep learning for sparse 3D data
Deep learning is widely applied to sparse 3D data to perform challenging tasks, e.g., 3D object detection and semantic segmentation. However, the high performance of deep learning comes with high costs, including computational costs and the effort to capture and label data. This work investigates and improves the efficiency of deep learning for sparse 3D data to overcome the obstacles to the further development of this technology.
