Crowdsourcing in Computer Vision

Crowdsourcing in Computer Vision PDF Author: Adriana Kovashka
Publisher:
ISBN: 9781680832136
Category : Artificial intelligence
Languages : en
Pages : 2

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Book Description
Computer vision systems require large amounts of manually annotated data to properly learn challenging visual concepts. Crowdsourcing platforms offer an inexpensive method to capture human knowledge and understanding, for a vast number of visual perception tasks. In this survey, we describe the types of annotations computer vision researchers have collected using crowdsourcing, and how they have ensured that this data is of high quality while annotation effort is minimized. We begin by discussing data collection on both classic (e.g., object recognition) and recent (e.g., visual story-telling) vision tasks. We then summarize key design decisions for creating effective data collection interfaces and workflows, and present strategies for intelligently selecting the most important data instances to annotate. Finally, we conclude with some thoughts on the future of crowdsourcing in computer vision.

Crowdsourcing in Computer Vision

Crowdsourcing in Computer Vision PDF Author: Adriana Kovashka
Publisher:
ISBN: 9781680832129
Category : Computers
Languages : en
Pages : 80

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Book Description
An overview of how crowdsourcing has been used in computer vision, enabling a computer vision researcher who has previously not collected non-expert data to devise a data collection strategy. It will also be of help to researchers who focus broadly on crowdsourcing to examine how the latter has been applied in computer vision.

Fusion in Computer Vision

Fusion in Computer Vision PDF Author: Bogdan Ionescu
Publisher: Springer Science & Business Media
ISBN: 3319056964
Category : Computers
Languages : en
Pages : 279

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Book Description
This book presents a thorough overview of fusion in computer vision, from an interdisciplinary and multi-application viewpoint, describing successful approaches, evaluated in the context of international benchmarks that model realistic use cases. Features: examines late fusion approaches for concept recognition in images and videos; describes the interpretation of visual content by incorporating models of the human visual system with content understanding methods; investigates the fusion of multi-modal features of different semantic levels, as well as results of semantic concept detections, for example-based event recognition in video; proposes rotation-based ensemble classifiers for high-dimensional data, which encourage both individual accuracy and diversity within the ensemble; reviews application-focused strategies of fusion in video surveillance, biomedical information retrieval, and content detection in movies; discusses the modeling of mechanisms of human interpretation of complex visual content.

Computer Vision – ECCV 2022

Computer Vision – ECCV 2022 PDF Author: Shai Avidan
Publisher: Springer Nature
ISBN: 3031200748
Category : Computers
Languages : en
Pages : 807

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Book Description
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow PDF Author: Aurélien Géron
Publisher: "O'Reilly Media, Inc."
ISBN: 109812247X
Category : Computers
Languages : en
Pages : 863

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Book Description
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

Crowdsourcing: Concepts, Methodologies, Tools, and Applications

Crowdsourcing: Concepts, Methodologies, Tools, and Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522583637
Category : Business & Economics
Languages : en
Pages : 1711

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Book Description
With the growth of information technology, many new communication channels and platforms have emerged. This growth has advanced the work of crowdsourcing, allowing individuals and companies in various industries to coordinate efforts on different levels and in different areas. Providing new and unique sources of knowledge outside organizations enables innovation and shapes competitive advantage. Crowdsourcing: Concepts, Methodologies, Tools, and Applications is a collection of innovative research on the methods and applications of crowdsourcing in business operations and management, science, healthcare, education, and politics. Highlighting a range of topics such as crowd computing, macrotasking, and observational crowdsourcing, this multi-volume book is ideally designed for business executives, professionals, policymakers, academicians, and researchers interested in all aspects of crowdsourcing.

Mobile Crowdsourcing

Mobile Crowdsourcing PDF Author: Jie Wu
Publisher: Springer Nature
ISBN: 3031323971
Category : Computers
Languages : en
Pages : 456

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Book Description
This book offers the latest research results in recent development on the principles, techniques and applications in mobile crowdsourcing. It presents state-of-the-art content and provides an in-depth overview of the basic background in this related field. Crowdsourcing involves a large crowd of participants working together to contribute or produce goods and services for the society. The early 21st century applications of crowdsourcing can be called crowdsourcing 1.0, which includes businesses using crowdsourcing to accomplish various tasks, such as the ability to offload peak demand, access cheap labor, generate better results in a timely matter, and reach a wider array of talent outside the organization. Mobile crowdsensing can be described as an extension of crowdsourcing to the mobile network to combine the idea of crowdsourcing with the sensing capacity of mobile devices. As a promising paradigm for completing complex sensing and computation tasks, mobile crowdsensing serves the vital purpose of exploiting the ubiquitous smart devices carried by mobile users to make conscious or unconscious collaboration through mobile networks. Considering that we are in the era of mobile internet, mobile crowdsensing is developing rapidly and has great advantages in deployment and maintenance, sensing range and granularity, reusability, and other aspects. Due to the benefits of using mobile crowdsensing, many emergent applications are now available for individuals, business enterprises, and governments. In addition, many new techniques have been developed and are being adopted. This book will be of value to researchers and students targeting this topic as a reference book. Practitioners, government officials, business organizations and even customers -- working, participating or those interested in fields related to crowdsourcing will also want to purchase this book.

Academic Crowdsourcing in the Humanities

Academic Crowdsourcing in the Humanities PDF Author: Mark Hedges
Publisher: Chandos Publishing
ISBN: 0081010451
Category : Social Science
Languages : en
Pages : 192

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Book Description
Academic Crowdsourcing in the Humanities lays the foundations for a theoretical framework to understand the value of crowdsourcing, an avenue that is increasingly becoming important to academia as the web transforms collaboration and communication and blurs institutional and professional boundaries. Crowdsourcing projects in the humanities have, for the most part, focused on the generation or enhancement of content in a variety of ways, leveraging the rich resources of knowledge, creativity, effort and interest among the public to contribute to academic discourse. This book explores methodologies, tactics and the "citizen science" involved. - Addresses crowdsourcing for the humanities and cultural material - Provides a systematic, academic analysis of crowdsourcing concepts and methodologies - Situates crowdsourcing conceptually within the context of related concepts, such as 'citizen science', 'wisdom of crowds', and 'public engagement'

Leveraging the Wisdom of the Crowd in Software Testing

Leveraging the Wisdom of the Crowd in Software Testing PDF Author: Mukesh Sharma
Publisher: CRC Press
ISBN: 1482254492
Category : Computers
Languages : en
Pages : 178

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Book Description
Its scale, flexibility, cost effectiveness, and fast turnaround are just a few reasons why crowdsourced testing has received so much attention lately. While there are a few online resources that explain what crowdsourced testing is all about, there's been a need for a book that covers best practices, case studies, and the future of this technique. Filling this need, Leveraging the Wisdom of the Crowd in Software Testing shows you how to leverage the wisdom of the crowd in your software testing process. Its comprehensive coverage includes the history of crowdsourcing and crowdsourced testing, implementation practices, and future trends. The book discusses best practices in implementation-explaining what, when, and how to crowdsource in a testing effort. It also includes case studies that illustrate how both product and service companies have successfully applied crowdsourcing in their testing programs. Explaining how to use the combined advantages of crowdsourcing and cloud computing for software testing, the book examines various engagement models in which you could implement crowdsourced testing. It addresses effective defect management in crowdsourced testing and considers both the business and engineering aspects of crowdsourced testing. The book explores the challenges, limitations, and situations when crowdsourced testing will not work and provides powerful best practices for mitigating the constraints and challenges, including how to build a crowdsourcing platform to test software products. Covering career opportunities for crowd testers, the book concludes by taking a look at the need to build a crowdsourced testing ecosystem, who the players of such an ecosystem would be, and who would need to champion such an effort.

Crowdsourced Data Management

Crowdsourced Data Management PDF Author: Adam Marcus
Publisher:
ISBN: 9781680830903
Category : Computers
Languages : en
Pages : 186

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Book Description
Crowdsourced Data Management: Industry and Academic Perspectives aims to narrow the gap between academics and practitioners in this burgeoning field. It simultaneously introduces academics to real problems that practitioners encounter every day, and provides a survey of the state of the art for practitioners to incorporate into their designs.

Seeing the Past with Computers

Seeing the Past with Computers PDF Author: Kevin Kee
Publisher: University of Michigan Press
ISBN: 0472131117
Category : Computers
Languages : en
Pages : 255

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Book Description
Recent developments in computer technology are providing historians with new ways to see—and seek to hear, touch, or smell—traces of the past. Place-based augmented reality applications are an increasingly common feature at heritage sites and museums, allowing historians to create immersive, multifaceted learning experiences. Now that computer vision can be directed at the past, research involving thousands of images can recreate lost or destroyed objects or environments, and discern patterns in vast datasets that could not be perceived by the naked eye. Seeing the Past with Computers is a collection of twelve thought-pieces on the current and potential uses of augmented reality and computer vision in historical research, teaching, and presentation. The experts gathered here reflect upon their experiences working with new technologies, share their ideas for best practices, and assess the implications of—and imagine future possibilities for—new methods of historical study. Among the experimental topics they explore are the use of augmented reality that empowers students to challenge the presentation of historical material in their textbooks; the application of seeing computers to unlock unusual cultural knowledge, such as the secrets of vaudevillian stage magic; hacking facial recognition technology to reveal victims of racism in a century-old Australian archive; and rebuilding the soundscape of an Iron Age village with aural augmented reality. This volume is a valuable resource for scholars and students of history and the digital humanities more broadly. It will inspire them to apply innovative methods to open new paths for conducting and sharing their own research.