The Uncertain Image

Citizens of networked societies are almost incessantly accompanied by ecologies of images. These ecologies of still and moving images present a paradox of uncertainties emerging along with certainties. Images appear more certain as the technical capacities that render them visible increase. At the same time, images are touched by more uncertainty as their numbers, manipulabilities, and contingencies multiply. With the emergence of big data, the image is becoming a dominant vehicle for the construction and presentation of the truth of data. Images present themselves as so many promises of the certainty, predictability, and intelligibility offered by data. The focus of this book is twofold. It analyses the kinds of images appearing today, showing how they are marked by a return to modern photographic emphases on high resolution, clarity, and realistic representation. Secondly, it discusses the ways in which the uncertainty of images is increasingly underscored within such reiterated emphases on allegedly certain visual truths. This often involves renewed encounters with noise, grain, glitch, blur, vagueness, and indistinctness. This book provides the reader with an intriguing transdisciplinary investigation of the uncertainly certain relation between the cultural imagination and the techno-aesthetic regime of big data and ubiquitous computing. This book was originally published as a special issue of Digital Creativity.

Almost all museums hold photographs in their collections, and museum professionals and their audiences engage with photographs in a myriad of ways. Yet despite some three decades of critical museology and photographic theory, and an extensive debate on the politics of representation, outside art museums, almost no critical attention has been given specifically to the roles, purposes and lives of these photographs within museums. This book brings into focus the ubiquitous yet entirely unconsidered work that photographs are put to in museums. The authors' argument is that there is an economy of photographs in museums which is integral to the processes of the museum, and integral to the understanding of museums. The international contributors, drawn from curators and academics, reflect a range of visual and museological expertise. After an introduction setting out the range of questions and problems, the first part addresses broad curatorial strategies and ways of thinking about photographs in museums. Shifting the emphasis from curatorial practices and anxieties to the space of the gallery, this is followed by a series of case studies of exhibitionary practices and the museum strategies that support them. The third section focuses on the role of photographs in the museum articulation of ’difficult histories’. A final section addresses photograph collections in a digital environment. New technologies and new media have transformed the management, address and purposing in photographs in museums, from cataloguing practices to streaming on social media. These growing practices challenge both traditional hierarchies of knowledge in museums and the location of authority about photographs. The volume emerges from PhotoCLEC, a HERA funded project on museums and the photographic legacy of the colonial past in a postcolonial and multicultural Europe.

"In the beginning, there was no real plan, just a road trip that became a journey." In the years 1986 and 1987, Keith Carter and his wife, Patricia, visited one hundred small Texas towns with intriguing names like Diddy Waw Diddy, Elysian Fields, and Poetry. He says, "I tried to make my working method simple and practical: one town, one photograph. I would take several rolls of film but select only one image to represent that dot on my now-tattered map. The titles of the photographs are the actual names of the small towns. . . ." Carter created a body of work that evoked the essence of small-town life for many people, including renowned playwright and fellow Texan, Horton Foote. In 1988, Carter published his one town/one picture collection in From Uncertain to Blue, a landmark book that won acclaim both nationally and internationally for the artistry, timelessness, and universal appeal of its images—and established Carter as one of America's most promising fine art photographers. Now a quarter century after the book's publication, From Uncertain to Blue has been completely re-envisioned and includes a new essay in which Carter describes how the search for photographic subjects in small towns gradually evolved into his first significant work as an artist. He also offers additional insight into his creative process by including some of his original contact sheets. And Patricia Carter gives her own perspective on their journey in her amplified notes about many of the places they visited as they discovered the world of possibilities from Uncertain to Blue.

What’s the best way to develop for a Web gone wild? That’s easy. Simply scrap the rules you’ve relied on all these years and embrace uncertainty as a core tenet of design. In this practical book, veteran developer Rob Larsen outlines the principles out what he calls The Uncertain Web, and shows you techniques necessary to successfully make the transition. By combining web standards, progressive enhancement, an iterative approach to design and development, and a desire to question the status quo, your team can create sites and applications that will perform well in a wide range of present and future devices. This guide points the way. Topics include: Navigating thousands of browser/device/OS combinations Focusing on optimal, not absolute solutions Feature detection, Modernizr, and polyfills RWD, mobile first, and progressive enhancement UIs that work with multiple user input modes Image optimization, SVG, and server-side options The horribly complex world of web video The Web we want to see in the future

The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.

Algebraic projective geometry, with its multilinear relations and its embedding into Grassmann-Cayley algebra, has become the basic representation of multiple view geometry, resulting in deep insights into the algebraic structure of geometric relations, as well as in efficient and versatile algorithms for computer vision and image analysis. This book provides a coherent integration of algebraic projective geometry and spatial reasoning under uncertainty with applications in computer vision. Beyond systematically introducing the theoretical foundations from geometry and statistics and clear rules for performing geometric reasoning under uncertainty, the author provides a collection of detailed algorithms. The book addresses researchers and advanced students interested in algebraic projective geometry for image analysis, in statistical representation of objects and transformations, or in generic tools for testing and estimating within the context of geometric multiple-view analysis.

Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.

This book identifies the important uncertainties to use in real-world problem modeling. Having information about several types of ambiguities, vagueness, and uncertainties is vital in modeling problems that involve linguistic variables, parameters, and word computing. Today, since most of our real-world problems are related to decision-making at the right time, we need to apply intelligent decision science. Clearly, in order to have an appropriate and flexible mathematical model, every intelligent system requires real data on our environment. Presenting problems that can be represented using mathematical models to create a system of linear equations, this book discusses the latest insights into uncertain information.

In image processing and computer vision applications such as medical or scientific image data analysis, as well as in industrial scenarios, images are used as input measurement data. It is good scientific practice that proper measurements must be equipped with error and uncertainty estimates. For many applications, not only the measured values but also their errors and uncertainties, should be—and more and more frequently are—taken into account for further processing. This error and uncertainty propagation must be done for every processing step such that the final result comes with a reliable precision estimate. The goal of this book is to introduce the reader to the recent advances from the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). It presents a concept with which error propagation and sensitivity analysis can be formulated with a set of basic operations. The approach discussed in this book has the potential for application in all areas of quantitative computer vision, image processing, and image analysis. In particular, it might help medical imaging finally become a scientific discipline that is characterized by the classical paradigms of observation, measurement, and error awareness. This book is comprised of eight chapters. After an introduction to the goals of the book (Chapter 1), we present a brief review of PDEs and their numerical treatment (Chapter 2), PDE-based image processing (Chapter 3), and the numerics of stochastic PDEs (Chapter 4). We then proceed to define the concept of stochastic images (Chapter 5), describe how to accomplish image processing and computer vision with stochastic images (Chapter 6), and demonstrate the use of these principles for accomplishing sensitivity analysis (Chapter 7). Chapter 8 concludes the book and highlights new research topics for the future.

This Handbook explores the cognitive, motivational, interpersonal, clinical, and applied aspects of personal uncertainty. It showcases both the diversity and the unity that defines contemporary perspectives on uncertainty in self within social and personality psychology. The contributions to the volume are all written by distinguished scholars in personality, social psychology, and clinical psychology united by their common focus on the causes and consequences of self-uncertainty. Chapters explore the similarities and differences between personal uncertainty and other psychological experiences in terms of their nature and relationship with human thought, emotion, motivation, and behavior. Specific challenges posed by personal uncertainty and the coping strategies people develop in their daily life are identified. There is an assessment of the potential negative and positive repercussions of coping with the specific experience of self-uncertainty, including academic, health, and relationship outcomes. Throughout, strategies specifically designed to assist others in confronting the unique challenges posed by self-uncertainty in ways that emphasize healthy psychological functioning and growth are promoted. In addition, the contributions to the Handbook touch on the psychological, social, and cultural context of the new millennium, including concepts such as Friedman’s "flat world," confidence, the absence of doubt in world leaders, the threat of terrorism since 9/11, the arts, doubt and religious belief, and views of doubt as the universal condition of humankind. The Handbook is an invaluable resource for researchers, practitioners, and senior undergraduate and graduate students in social and personality psychology, clinical and counseling psychology, educational psychology, and developmental psychology.