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Author: Joanna Zylinska
Publisher: MIT Press
ISBN: 0262546833
Category : Social Science
Languages : en
Pages : 288
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Book Description
A provocative investigation of the future of photography and human perception in the age of AI. We are constantly photographing and being photographed while feeding machine learning databases with our data, which in turn is used to generate new images. Analyzing the transformation of photography by computation—and the transformation of human perception by algorithmically driven images, from CGI to AI—The Perception Machine investigates what it means for us to live surrounded by image flows and machine eyes. In an astute and engaging argument, Joanna Zylinska brings together media theory and neuroscience in a Vilém Flusser–Paul Virilio remix. Her “perception machine” names a technical universe of images and their infrastructures. But it also refers to a sociopolitical condition resulting from today’s automation of vision, imaging—and imagination. Written by a theorist-practitioner, the book incorporates Zylinska’s own art projects, some of which have been co-created with AI. The photographs, collages, films, and installations available as part of the book (and its companion website) provide a different mode of thinking about our technological futures, at a local as well as a planetary level. Offering provocative concepts such as eco-eco-punk, AUTO-FOTO-KINO, planetary micro-vision, loser images, and sensography, the book outlines an existential philosophy of messy media for a time when our practices of imaging and self-imaging are being radically redesigned. Importantly, it also offers a new vision of our future.
Author: Joanna Zylinska
Publisher: MIT Press
ISBN: 0262546833
Category : Social Science
Languages : en
Pages : 288
Get Book Here
Book Description
A provocative investigation of the future of photography and human perception in the age of AI. We are constantly photographing and being photographed while feeding machine learning databases with our data, which in turn is used to generate new images. Analyzing the transformation of photography by computation—and the transformation of human perception by algorithmically driven images, from CGI to AI—The Perception Machine investigates what it means for us to live surrounded by image flows and machine eyes. In an astute and engaging argument, Joanna Zylinska brings together media theory and neuroscience in a Vilém Flusser–Paul Virilio remix. Her “perception machine” names a technical universe of images and their infrastructures. But it also refers to a sociopolitical condition resulting from today’s automation of vision, imaging—and imagination. Written by a theorist-practitioner, the book incorporates Zylinska’s own art projects, some of which have been co-created with AI. The photographs, collages, films, and installations available as part of the book (and its companion website) provide a different mode of thinking about our technological futures, at a local as well as a planetary level. Offering provocative concepts such as eco-eco-punk, AUTO-FOTO-KINO, planetary micro-vision, loser images, and sensography, the book outlines an existential philosophy of messy media for a time when our practices of imaging and self-imaging are being radically redesigned. Importantly, it also offers a new vision of our future.
Author: Zbigniew Les
Publisher: Springer
ISBN: 3030240703
Category : Technology & Engineering
Languages : en
Pages : 229
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Book Description
This unique book discusses machine understanding (MU). This new branch of classic machine perception research focuses on perception that leads to understanding and is based on the categories of sensory objects. In this approach the visual and non-visual knowledge, in the form of visual and non-visual concepts, is used in the complex reasoning process that leads to understanding. The book presents selected new concepts, such as perceptual transformations, within the machine understanding framework, and uses perceptual transformations to solve perceptual problems (visual intelligence tests) during understanding, where understanding is regarded as an ability to solve complex visual problems described in the authors’ previous books. Thanks to the uniqueness of the research topics covered, the book appeals to researchers from a wide range of disciplines, especially computer science, cognitive science and philosophy.
Author: Bruno Apolloni
Publisher: Springer Science & Business Media
ISBN: 9783540265498
Category : Technology & Engineering
Languages : en
Pages : 370
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Book Description
This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics such as intelligent object detection, foveated vision systems, online learning paradigms, reinforcement learning for a mobile robot, object tracking and motion estimation, 3D model construction, computer vision system and user modelling using dialogue strategies. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.
Author: Baochang Zhang
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110595567
Category : Computers
Languages : en
Pages : 152
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Book Description
The book provides an up-to-date on machine learning and visual perception, including decision tree, Bayesian learning, support vector machine, AdaBoost, object detection, compressive sensing, deep learning, and reinforcement learning. Both classic and novel algorithms are introduced. With abundant practical examples, it is an essential reference to students, lecturers, professionals, and any interested lay readers.
Author: Guido Tascini
Publisher: World Scientific
ISBN: 9814547921
Category :
Languages : en
Pages : 218
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Book Description
As perception stands for the acquisition of a real world representation by interaction with an environment, learning is the modification of this internal representation.This book highlights the relation between perception and learning and describes the influence of the learning in the interaction with the environment.Besides, this volume contains a series of applications of both machine learning and perception, where the former is often embedded in the latter and vice-versa.Among the topics covered, there are visual perception for autonomous robots, model generation of visual patterns, attentional reasoning, genetic approaches and various categories of neural networks.
Author: Gokhan Tur
Publisher: John Wiley & Sons
ISBN: 1119993946
Category : Language Arts & Disciplines
Languages : en
Pages : 443
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Book Description
Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal processing, pattern recognition, machine learning and artificial intelligence. SLU systems are designed to extract the meaning from speech utterances and its applications are vast, from voice search in mobile devices to meeting summarization, attracting interest from both commercial and academic sectors. Both human/machine and human/human communications can benefit from the application of SLU, using differing tasks and approaches to better understand and utilize such communications. This book covers the state-of-the-art approaches for the most popular SLU tasks with chapters written by well-known researchers in the respective fields. Key features include: Presents a fully integrated view of the two distinct disciplines of speech processing and language processing for SLU tasks. Defines what is possible today for SLU as an enabling technology for enterprise (e.g., customer care centers or company meetings), and consumer (e.g., entertainment, mobile, car, robot, or smart environments) applications and outlines the key research areas. Provides a unique source of distilled information on methods for computer modeling of semantic information in human/machine and human/human conversations. This book can be successfully used for graduate courses in electronics engineering, computer science or computational linguistics. Moreover, technologists interested in processing spoken communications will find it a useful source of collated information of the topic drawn from the two distinct disciplines of speech processing and language processing under the new area of SLU.
Author: Horst Bunke
Publisher: World Scientific
ISBN: 9814491470
Category : Computers
Languages : en
Pages : 246
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Book Description
Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).
Author:
Publisher:
ISBN: 9780127412528
Category :
Languages : en
Pages :
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Book Description
Author: Mark Last
Publisher: World Scientific
ISBN: 9814482609
Category : Computers
Languages : en
Pages : 221
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Book Description
An inadequate infrastructure for software testing is causing major losses to the world economy. The characteristics of software quality problems are quite similar to other tasks successfully tackled by artificial intelligence techniques. The aims of this book are to present state-of-the-art applications of artificial intelligence and data mining methods to quality assurance of complex software systems, and to encourage further research in this important and challenging area.
Author: Oded Z Maimon
Publisher: World Scientific
ISBN: 9814590096
Category : Computers
Languages : en
Pages : 328
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Book Description
Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:
