The well-illustrated articles in Observing the World through Images offer insights into the uses of images in astronomy, mathematics, instrument-making, medicine and alchemy, highlighting shared forms as well as those peculiar to individual disciplines. Themes addressed include: the processes of image production and communication; the transformation of images through copying and adaptation for new purposes; genres and traditions of imagery in particular scientific disciplines; the mnemonic and pedagogical value of diagrams; the relationship between text and image; and the roles of diagrams as tools to think with. Contributors include: Isabelle Pantin, Jennifer Rampling, Samuel Gessner, Renee Raphael, Karin Ekholm, Hester Higton, and Katie Taylor.

A timely and accessible synthesis of the strengths, weaknesses and reality of science through the eyes of a practicing scientist.

Observation and conceptual interpretation constitute the two major ways through which human beings engage the world. The World Observed/The World Conceived presents an innovative analysis of the nature and role of observation and conceptualization. While these two actions are often treated as separate, Hans Radder shows that they are inherently interconnected-that materially realized observational processes are always conceptually interpreted and that the meaning of concepts depends on the way they structure observational processes and abstract from them. He examines the role of human action and conceptualization in realizing observational processes and develops a detailed theory of the relationship between observation, abstraction, and the meaning of concepts. The World Observed/The World Conceived will prove useful to many areas of scholarly study including ontology, epistemology, philosophy of language, philosophy of science, science studies, and cognitive science.

In this unprecedented book, a gifted animal scientist who is also autistic, delivers a report on autism, written from her unique perspective. What emerges is the document of an extraordinary human being, one who bridges the gulf between her condition and our own, shedding light on the riddle of our common identity.

Contains seven essays. Three of them use only pictures. Examines the relationship between what we see and what we know.

Understanding World Regional Geography (UWRG) is a course designed to teach students to think and apply geographic concepts long after the course is over. Author Erin Fouberg draws from her expertise in geography education and research in student learning to create a product that has a strong pedagogical framework designed to engage students and deepen their understanding of the world by having them “DO” Geography. UWRG includes features that help students learn to read cultural and physical landscapes, ask geographic questions, apply geographic concepts, and make connections. It integrates 25 threshold concepts and teaches students how geographers apply these concepts and asks them to apply these concepts themselves. This enables them to grasp the complexities of the world and provides them with the knowledge and thinking skills necessary to understanding it. UWRG is the first introductory course to integrate ESRI ArcGIS Online thematic maps, enabling students to engage with course materials, see patterns, and answer geographic questions.

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques.