Illustration Research Methods
Illustration Research Methods

Author: Rachel Gannon

Publisher: Bloomsbury Publishing

Published: 2020-12-20

Total Pages: 226

ISBN-13: 1350051454

DOWNLOAD EBOOK

**Shortlisted for the 2021 British Book Design and Production Awards for the Best Jacket / Cover Design** For years illustration has lacked a strong critical history in which to frame it, with academics and media alike assessing it as part of design rather than a discipline in its own right. Illustration Research Methods addresses this void and adds to a fast-emerging discipline, establishing a lexicon that is specific to discussing contemporary illustration practice and research. The chapters are broken down into the various roles that exist within the industry and which illustration research can draw from, such as 'Reporting' and 'Education'. In doing so, users are able to explore a diverse range of disciplines that are rich in critical theory and can map these existing research methodologies to their own study and practice. Supported by a wealth of case studies from international educators, student projects sit alongside those of world-renowned illustrators. Thus allowing users the opportunity to put what they have learnt into context and offering insight into the thinking and techniques behind some of illustrations' greats.

Case-Based Reasoning on Images and Signals
Case-Based Reasoning on Images and Signals

Author: Petra Perner

Publisher: Springer Science & Business Media

Published: 2008

Total Pages: 442

ISBN-13: 3540731784

DOWNLOAD EBOOK

This book is the ?rst edited book that deals with the special topic of signals and images within case-based reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statisticalandknowledge-basedtechniqueslackrobustness,accuracy,and?- ibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBRstrategiesintosignal-interpretingsystemscansatisfytheserequirements. CBR can be used to control the signal-processing process in all phases of a signal-interpreting system to derive information of the highest possible qu- ity. Beyond this CBR o?ers di?erent learning capabilities, for all phases of a signal-interpretingsystem,thatsatisfydi?erentneedsduringthedevelopment process of a signal-interpreting system. In the outline of this book we summarize under the term “signal” signals of 1-dimensional, 2-dimensional or 3-dimensional nature. The unique data and the necessary computation techniques require ext- ordinary case representations, similarity measures and CBR strategies to be utilised. Signalinterpretation(1D,2D,or3Dsignalinterpretation)istheprocessof mapping the numerical representation of a signal into logical representations suitable for signal descriptions. A signal-interpreting system must be able to extract symbolic features from the raw data e.g., the image (e.g., irregular structure inside the nodule, area of calci?cation, and sharp margin). This is a complex process; the signal passes through several general processing steps before the ?nal symbolic description is obtained. The structure of the book is divided into a theoretical part and into an application-oriented part.