881 resultados para knowing-what (pattern recognition) element of knowing-how knowledge


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The majority of current applications of neural networks are concerned with problems in pattern recognition. In this article we show how neural networks can be placed on a principled, statistical foundation, and we discuss some of the practical benefits which this brings.

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The majority of current applications of neural networks are concerned with problems in pattern recognition. In this article we show how neural networks can be placed on a principled, statistical foundation, and we discuss some of the practical benefits which this brings.

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Human object recognition is considered to be largely invariant to translation across the visual field. However, the origin of this invariance to positional changes has remained elusive, since numerous studies found that the ability to discriminate between visual patterns develops in a largely location-specific manner, with only a limited transfer to novel visual field positions. In order to reconcile these contradicting observations, we traced the acquisition of categories of unfamiliar grey-level patterns within an interleaved learning and testing paradigm that involved either the same or different retinal locations. Our results show that position invariance is an emergent property of category learning. Pattern categories acquired over several hours at a fixed location in either the peripheral or central visual field gradually become accessible at new locations without any position-specific feedback. Furthermore, categories of novel patterns presented in the left hemifield are distinctly faster learnt and better generalized to other locations than those learnt in the right hemifield. Our results suggest that during learning initially position-specific representations of categories based on spatial pattern structure become encoded in a relational, position-invariant format. Such representational shifts may provide a generic mechanism to achieve perceptual invariance in object recognition.

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We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding.

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We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding.

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Earlier the authors have suggested a logical level description of classes which allows to reduce a solution of various pattern recognition problems to solution of a sequence of one-type problems with the less dimension. Here conditions of the effectiveness of the use of such a level descriptions are proposed.

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The problem of decision functions quality in pattern recognition is considered. An overview of the approaches to the solution of this problem is given. Within the Bayesian framework, we suggest an approach based on the Bayesian interval estimates of quality on a finite set of events.

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The paper is devoted to the description of hybrid pattern recognition method developed by research groups from Russia, Armenia and Spain. The method is based upon logical correction over the set of conventional neural networks. Output matrices of neural networks are processed according to the potentiality principle which allows increasing of recognition reliability.

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The trees, hedgerows and woods are current configuration of the tree network in several ecological regions of the world. In Trás–os–Montes region, Northeast of Portugal, they are a traditional component of Terra fria landscape and they could be seen in several forms: scatter trees, fencerows, small woodlots, riparian buffer strips, among others. The extensive livestock systems in this region are based on a set of circuits across the landscape. In this practice, flocks interacts with these structures using them for different functions inducing an influence on the itineraries. Our purpose will be focused on the woody features of landscape regarding their configurations, abundance and spacial distribution; in order to examine how the grazing systems depends on the currency of these formations; particularly how species flocks behaviors are related on. Depending on spatial data, The investigation attain to compare the tree network within the agriculture matrix, to the grazed territory crossed by flocks. From the other side, the importance of spatial data on interpreting the issue by suggesting different parameter that may influence the circuits. The recognition of the pressure exerciced by the occurence of the woody structures on the grazed circuits is possible. We believe that the role of these woody structures features in supporting the tradicional silvopastoral systems has been sufficiently strong for change their distribution pattern.

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Close similarities have been found between the otoliths of sea-caught and laboratory-reared larvae of the common sole Solea solea (L.), given appropriate temperatures and nourishment of the latter. But from hatching to mouth formation. and during metamorphosis, sole otoliths have proven difficult to read because the increments may be less regular and low contrast. In this study, the growth increments in otoliths of larvae reared at 12 degrees C were counted by light microscopy to test the hypothesis of daily deposition, with some results verified using scanning electron microscopy (SEM), and by image analysis in order to compare the reliability of the 2 methods in age estimation. Age was first estimated (in days posthatch) from light micrographs of whole mounted otoliths. Counts were initiated from the increment formed at the time of month opening (Day 4). The average incremental deposition rate was consistent with the daily hypothesis. However, the light-micrograph readings tended to underestimate the mean ages of the larvae. Errors were probably associated with the low-contrast increments: those deposited after the mouth formation during the transition to first feeding, and those deposited from the onset of eye migration (about 20 d posthatch) during metamorphosis. SEM failed to resolve these low-contrast areas accurately because of poor etching. A method using image analysis was applied to a subsample of micrograph-counted otoliths. The image analysis was supported by an algorithm of pattern recognition (Growth Demodulation Algorithm, GDA). On each otolith, the GDA method integrated the growth pattern of these larval otoliths to averaged data from different radial profiles, in order to demodulate the exponential trend of the signal before spectral analysis (Fast Fourier Transformation, FFT). This second method both allowed more precise designation of increments, particularly for low-contrast areas, and more accurate readings but increased error in mean age estimation. The variability is probably due to a still rough perception of otolith increments by the GDA method, counting being achieved through a theoretical exponential pattern and mean estimates being given by FFT. Although this error variability was greater than expected, the method provides for improvement in both speed and accuracy in otolith readings.

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The objective of he article is to research the dynamic capacities developed and used by WEG in its internationalization process and to explain how these capacities help the company defends and supports competitive advantage. The article presents an exploratory study of the internationalization process of WEG in Argentina and China. This article has as analysis approach the dynamic capacities, contributes to the literature of international management in two aspects. First, it adds the analytical look of the internationalization based on dynamic capacities that are still well restricted. Second, when working the dynamic capacities as central element of the analysis of the internationalization process, it Proposes one framework of integrative analysis of the economic and behavioral theories that are used to explain the process of companies`-internationalization, although they are dealt independently and sometimes antagonistic way. The result shows as the dynamic capacities are articulated in the base of WEG in its process of internationalization for Argentina and the subsequent movement for China. The developed dynamic capacities in Argentina were acquired for the Brazilian headquarter and could have been applied in the process of internationalization for China. However, a more complex organizational structure cannot be identified where the inter-subsidiary relationships could share dynamic capacities as proposed in framework.

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Abstract This article provides a comprehensive picture of IR in South America by applying content analysis to 7,857 articles published in 35 journals from six South American countries from 2006 to 2014 in order to discover what the predominant theories, methods and research areas in this field are, how scholars tend to combine them in their research designs, and what the profiles of regional journals are, regarding their epistemological, methodological and subject preferences. The findings reveal a predominantly Positivist and largely Qualitative discipline, resembling North American and European IR.