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Switch to: References
Citations of:
Image-based object recognition in man, monkey and machine
Cognition 67 (1-2):1-20 (1998)
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Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) |
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This paper comments on an article by V.S. Ramachandran and William Hirstein (JCS,1999) in which they purport to be identifying the neurological principles of beauty. I draw attention to the way the problem of beauty is construed in the philosophical literature by Mary Mothersill (1984) and Immanuel Kant (Critique of Judgment). I argue that Ramachandran and Hirsteins' principles do not address the problem of beauty because they do not differentiate between the experience of beauty and other closely related phenomena. I (...) |
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Visualizing and mental imagery are thought to be cognitive states by all sides of the imagery debate. Yet the phenomenology of those states has distinctly visual ingredients. This has potential consequences for the hypothesis that vision is cognitively impenetrable, the ability of visual processes to ground perceptual warrant and justification, and the distinction between cognitive and perceptual phenomenology. I explore those consequences by describing two forms of visual ambiguity that involve visualizing: the ability to visually experience a picture surface as (...) |
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The late vision theorist David Marr identified three levels of explanation that he argued needed to be addressed in order to understand vision : (i) the psychological, functional or computational level of processes; (ii) the physical or neurological which is the level of explanation employed by Zeki; and (iii) the algorithmic – the level of implementation. For Zeki’s purpose of drawing upon vision-theory in order to better understand art and aesthetics, there is no need to focus on the third level. (...) |
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Traditionally, theories of concepts in psychology assume that concepts are a single, uniform kind of mental representation. But no single kind of representation can explain all of the empirical data for which concepts are responsible. I argue that the assumption that concepts are uniformly the same kind of mental structure is responsible for these theories’ shortcomings, and outline a pluralist theory of concepts that rejects this assumption. On pluralism, concepts should be thought of as being constituted by multiple representational kinds, (...) |
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This paper investigates a the cognitive foundations of a pragmatic account of line drawings. It sets to highlight those features of line drawings that make them, as opposed to other types of visual representations, particularly conducive to communication. It is argued that representational and artifactual properties of drawings must be investigated together in order to understand the peculiarities of drawings as communicative tools. |
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Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and (...) |
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From the viewpoint of pattern recognition and computational learning, mirror neurons form an interesting multimodal representation that links action perception and planning. While it seems unlikely that all details of such representations are specified by the genetic code, robust learning of such complex representations likely requires an appropriate interplay between plasticity, generalization, and anatomical constraints of the underlying neural architecture. |
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Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge lengths computed using various distance measures. Feature distinctiveness was computed as a distance measure, showing how far an object in a network is from other objects based on (...) |
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Drawing — and I speak here of outline drawing that uses just lines: monochrome, with no particular concern for what fills the spaces left between the lines — is a human artifact as ancient as it is mysterious. Even a simple enumeration of facts about it is bound to arouse interest and theoretical curiosity. Here are a few. Drawings are just as old as the oldest human representations known to us. The painted animals in the caves of Lascaux and Chauvet (...) |
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