Cognition And Recognition

The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition. These interconnected essays on three-dimensional visual object recognition present cutting-edge research by some of the most creative neuroscientific, cognitive, and computational scientists in the field. Cassandra Moore and Patrick Cavanagh take a classic demonstration, the perception of "two-tone" images, and turn it into a method for understanding the nature of object representations in terms of surfaces and the interaction between bottom-up and top-down processes. Michael J. Tarr and Isabel Gauthier use computer graphics to study whether viewpoint-dependent recognition mechanisms can generalize between exemplars of perceptually defined classes. Melvyn A. Goodale and G. Keith Humphrey use innovative psychophysical techniques to investigate dissociable aspects of visual and spatial processing in brain-injured subjects. D.I. Perrett, M.W. Oram, and E. Ashbridge combine neurophysiological single-cell data from monkeys with computational analyses for a new way of thinking about the mechanisms that mediate viewpoint-dependent object recognition and mental rotation. Shimon Ullman also addresses possible mechanisms to account for viewpoint-dependent behavior, but from the perspective of machine vision. Finally, Philippe G. Schyns synthesizes work from many areas, to provide a coherent account of how stimulus class and recognition task interact. The contributors bring a wide range of methodologies to bear on the common problem of image-based object recognition.

Mainstream cognitive science claims that the essence of human cognition is its capacity to categorize the world into stones, trees, friends and foes, elements that form more or less homogeneous groups. But it has seldom been asked how individual entities like one's father or a work of art are in their uniqueness (or specificity) represented mentally, if at all. This book tackles that problem by surveying data and theories coming from various fields such as evolutionary biology, psychology, neurology and philosophy, and fitting them into a coherent, new theoretical framework of a broadly anti-representationalist ilk. In order to construct the framework, the authors introduce a series of new notions, reshape or interpret many already in currency (such as affordances, categories, misrepresentation, conceptual and non-conceptual content, aspect seeing, the analog-digital distinction and the evolutionary adaptivity of art), and formulate five criteria on the basis of which what is and what is not mentally represented can clearly be told apart. The book will be of interest to cognitive scientists in general.

Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In this book, Shimon Ullman focuses on the processes of high-level vision that deal with the interpretation and use of what is seen in the image. In particular, he examines two major problems. The first, object recognition and classification, involves recognizing objects despite large variations in appearance caused by changes in viewing position, illumination, occlusion, and object shape. The second, visual cognition, involves the extraction of shape properties and spatial relations in the course of performing visual tasks such as object manipulation, planning movements in the environment, or interpreting graphical material such as diagrams, graphs and maps. The book first takes up object recognition and develops a novel approach to the recognition of three-dimensional objects. It then studies a number of related issues in high-level vision, including object classification, scene segmentation, and visual cognition. Using computational considerations discussed throughout the book, along with psychophysical and biological data, the final chapter proposes a model for the general flow of information in the visual cortex. Understanding vision is a key problem in the brain sciences, human cognition, and artificial intelligence. Because of the interdisciplinary nature of the theories developed in this work, High-Level Vision will be of interest to readers in all three of these fields.

Annotation In 1997, Rakover (U. of Haifa) and Cahlon (Oakland U, Michigan) won an award from the Minister of Internal Security of the State of Israel for developing the Catch model for face recognition. Since then they have proposed the law of Face Recognition by Similarity. Here they describe the computer and mathematical research they have conducted and some of their results. Annotation c. Book News, Inc., Portland, OR (booknews.com).

The book covers a comprehensive overview of the theory, methods, applications and tools of cognition and recognition. The book is a collection of best selected papers presented in the International Conference on Cognition and Recognition 2016 (ICCR 2016) and helpful for scientists and researchers in the field of image processing, pattern recognition and computer vision for advance studies. Nowadays, researchers are working in interdisciplinary areas and the proceedings of ICCR 2016 plays a major role to accumulate those significant works at one place. The chapters included in the proceedings inculcates both theoretical as well as practical aspects of different areas like nature inspired algorithms, fuzzy systems, data mining, signal processing, image processing, text processing, wireless sensor networks, network security and cellular automata.

This monograph demonstrates the interplay between Shannon information and semantic information in cognition. It shows that Shannon’s information acts as driving force for the formation of semantic information; and vice versa, namely, that semantic information participates in the formation of Shannonian information. The authors show that in cognition, Shannonian and semantic information are interrelated as two aspects of a cognitive process termed as information adaptation. In the latter the mind/brain adapts to the environment by the deflating and/or inflating of the information conveyed by the environment. In the process of information adaptation, quantitative variations in Shannon’s information entail different meanings while different meanings affect the quantity of information. The book illustrates the above conceptually and mathematically by reference to three cognitive processes: pattern recognition, face learning and the recognition of a moving object.

An argument that there are perceptual mechanisms that retrieve information in cognitively and conceptually unmediated ways and that this sheds light on various philosophical issues. In Cognition and Perception, Athanassios Raftopoulos discusses the cognitive penetrability of perception and claims that there is a part of visual processes (which he calls “perception”) that results in representational states with nonconceptual content; that is, a part that retrieves information from visual scenes in conceptually unmediated, “bottom-up,” theory-neutral ways. Raftopoulos applies this insight to problems in philosophy of science, philosophy of mind, and epistemology, and examines how we access the external world through our perception as well as what we can know of that world. To show that there is a theory-neutral part of existence, Raftopoulos turns to cognitive science and argues that there is substantial scientific evidence. He then claims that perception induces representational states with nonconceptual content and examines the nature of the nonconceptual content. The nonconceptual information retrieved, he argues, does not allow the identification or recognition of an object but only its individuation as a discrete persistent object with certain spatiotemporal properties and other features. Object individuation, however, suffices to determine the referents of perceptual demonstratives. Raftopoulos defends his account in the context of current discussions on the issue of the theory-ladenness of perception (namely the Fodor-Churchland debate), and then discusses the repercussions of his thesis for problems in the philosophy of science. Finally, Raftopoulos claims that there is a minimal form of realism that is defensible. This minimal realism holds that objects, their spatiotemporal properties, and such features as shape, orientation, and motion are real, mind-independent properties in the world.