996 resultados para Texture recognition
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1. In the present study, we investigated the short- and long-term effects of extremely low-frequency (ELF) magnetic fields on spatial recognition memory in mice by using a two-trial recognition Y-maze that is based on the innate tendency of rodents to exp
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In most studies regarding the improving or therapeutical effects induced by enriched environment (EE), EE was performed after the stress treatment or in patients with certain diseases. In the current study, the effects of chronic restraint stress (6 h/day) in mice living in an enriched environment or standard environment (SE) were tested. Mice were randomly divided into 4 groups: non-stressed or stressed mice housed in SE or EE conditions (SE, stress + SE, EE, stress + EE). Prepulse inhibition (PPI) of startle was tested after the 2 weeks or 4 weeks stress and/or EE treatment and 1 or 2 weeks withdrawal from the 4 weeks treatment. After the 4 weeks treatment, spatial recognition memory in Y-maze was also tested. The results showed that EE increased PPI in stressed and non-stressed mice after 2 weeks treatment. No effect of EE on PPI was found after the 4 weeks treatment. 4 weeks chronic restraint stress increased PPI in mice housed in standard but not EE conditions. Stressed mice showed deficits on the 1 h delay version of the Y-maze which could be prevented by living in an enriched environment. Our results indicated that living in an enriched environment reversed the impairing effects of chronic restraint stress on spatial recognition memory. However, EE did not change the effects of stress on PPI. (C) 2010 Elsevier B.V. All rights reserved.
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Global information is considered the primitive of visual perception in Gestalt psychology. Further, L. Chen ( 2005) proposed a new theory of topological visual perception. According to this theory, the perception of topological difference is faster than o
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本文选用经过实验验证的碱基序列 ,用简化的方式 ,构建了被水分子和镁离子修饰的核酸序列的分子模型 ,应用分子力学模拟方法对序列进行能量优化 ,对优化后序列的构象参数、成键状况和能量数据等进行了分析。对tRNAHHis GUG的识别特性作了初步的探索 ,得到了和实验结果相近的结论。此外 ,还从能力学的角度讨论了溶剂 -溶质 -溶剂相互作用形成的网状氢键网络对核酸结构稳定性的影响 ,探讨了非Crick_WatsonGU、UU配对的能力学特征并存在于被水分子和镁离子修饰的核酸序列中的GU、UU配对情况。
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In this paper, a novel cortex-inspired feed-forward hierarchical object recognition system based on complex wavelets is proposed and tested. Complex wavelets contain three key properties for object representation: shift invariance, which enables the extraction of stable local features; good directional selectivity, which simplifies the determination of image orientations; and limited redundancy, which allows for efficient signal analysis using the multi-resolution decomposition offered by complex wavelets. In this paper, we propose a complete cortex-inspired object recognition system based on complex wavelets. We find that the implementation of the HMAX model for object recognition in [1, 2] is rather over-complete and includes too much redundant information and processing. We have optimized the structure of the model to make it more efficient. Specifically, we have used the Caltech 5 standard dataset to compare with Serre's model in [2] (which employs Gabor filter bands). Results demonstrate that the complex wavelet model achieves a speed improvement of about 4 times over the Serre model and gives comparable recognition performance. © 2011 IEEE.
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We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.
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This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a real and challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2011 IEEE.
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Seven sets of protein target sites, which occur in several gene promoters, have been analyzed. The results suggest that there is a possible mode of specific recognition of double-helical nucleic acids by proteins, This recognition mode is related to a spe
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Model compensation methods for noise-robust speech recognition have shown good performance. Predictive linear transformations can approximate these methods to balance computational complexity and compensation accuracy. This paper examines both of these approaches from a variational perspective. Using a matched-pair approximation at the component level yields a number of standard forms of model compensation and predictive linear transformations. However, a tighter bound can be obtained by using variational approximations at the state level. Both model-based and predictive linear transform schemes can be implemented in this framework. Preliminary results show that the tighter bound obtained from the state-level variational approach can yield improved performance over standard schemes. © 2011 IEEE.