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Description: 2007年新东方英语的讲义，包括词汇，阅读，完形，有意考研者可以-2007 Oriental English handouts, including vocabulary, reading, Gestalt, interested persons can look at taking tests for
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Size: 1396958 |
Author: 李旋 |
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Description: 2007年新东方英语的讲义，包括词汇，阅读，完形，有意考研者可以-2007 Oriental English handouts, including vocabulary, reading, Gestalt, interested persons can look at taking tests for
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Size: 1396736 |
Author: 李旋 |
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Description: 格式塔心理学的经典著作，可作为心理学，模式识别，计算机视觉，等学科的参考书。-Gestalt psychology, classics, can be used as psychology, pattern recognition, computer vision, such as reference books disciplines.
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Size: 1443840 |
Author: 安向京 |
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Description: 基于Gestalt laws的图像显著边界监测和分割技术，适合于做区域和边界信息的图像处理学者参考，请一起分享-Based on Gestalt laws marked the boundary of image segmentation techniques for monitoring and suitable for the regional and boundary information to do image processing and scholars reference, please share
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Size: 5790720 |
Author: 单昊 |
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Description: 一个简单易用的应用配置库程序，由C++编写，运行于VS2005、2008环境。-A simple to use library for application configuration
Gestalt.Net was developed to be a simple to use library for application configuration. It allows for more flexibility, easier to use, and more powerful than the app.config/web.config, registry, or INI files. It handles encryption of config files automatically. Also due to its OO approach, most changes, etc. can be dealt with in code instead of modifying an XML file.
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Size: 772096 |
Author: athere |
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Description: 一个基于布尔图的显著性检测模型这个模型利用了全局拓扑测度，这一拓扑测度已经被证明了有助于感知的图形-背景分割。如格式塔心理学研究表明，如下因素很可能会影响图形-背景分割：大小，surroundedness，convexity, symmtry。本文研究surroundedness cue在显著性检测中的应用。 surroundedness的本质是图形和背景之间的enclosure topological relationship，能够被很好地定义，并且对不同的变化具有不变性（不懂）。 为了衡量surroundedness，BMS用二值图像集合表示图像。在BMS中，一个注意图(attention map)通过二值图处理技术激活给定的布尔图中的具有closed outer contours的区域来计算获得。显著性则根据期望注意图获得，也就是平均注意图。这个平均主义通过后续的处理可以用注视点的预测或是显著对象的检测。-A novel Boolean Map based Saliency (BMS) model is
proposed. An image is characterized by a set of binary
images, which are generated by randomly thresholding the
image’s color channels. Based on a Gestalt principle of
figure-ground segregation, BMS computes saliency maps
by analyzing the topological structure of Boolean maps.
BMS is simple to implement and efficient to run. Despite
its simplicity, BMS consistently achieves state-of-the-art
performance compared with ten leading methods on five eye
tracking datasets. Furthermore, BMS is also shown to be
advantageous in salient object detection.
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Size: 859136 |
Author: 焦玲玲 |
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