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Description: Matlab drawing of a class type Koch curve of matlab, a kind of Koch curve
Platform: |
Size: 5120 |
Author: Chiernrchy |
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Description: 新的自下而上的视dmits combination with other maps. The model is simple, and biologically plausible
insofar as it is naturally parallelized. This model powerfully predicts human
xations on 749 variations of 108 natural images, achieving 98% of the ROC area
of a human-based control, whereas the classical algorithms of Itti & Koch ([2],
[3], [4]) achieve only 84%.觉显著性模型，基于视觉显著图（GBVS），提出了。(A new bottom-up visual saliency model, Graph-Based Visual Saliency (GBVS), is
proposed. It consists of two steps: rst forming activation maps on certain feature
channels, and then normalizing them in a way which highlights conspicuity and
admits combination with other maps. The model is simple, and biologically plausible
insofar as it is naturally parallelized. This model powerfully predicts human
xations on 749 variations of 108 natural images, achieving 98% of the ROC area
of a human-based control, whereas the classical algorithms of Itti & Koch ([2],
[3], [4]) achieve only 84%.)
Platform: |
Size: 9145344 |
Author: 还有叫二哈的
|
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Description: 用matlab画的一个类式koch的曲线 Matlab, a kind of Koch curve(Matlab drawing of a class type Koch curve of matlab, a kind of Koch curve)
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Size: 6144 |
Author: zawdy
|
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Description: gbvs_nips 基于图的显著性。Graph-Based Visual Saliency。是发表在2006年NIPS上的论文。(A new bottom-up visual saliency model, Graph-Based Visual Saliency (GBVS), is proposed. It consists of two steps: first forming activation maps on certain feature channels, and then normalizing them in a way which highlights conspicuity and admits combination with other maps. The model is simple, and biologically plausible insorfar as it is naturally parallelized. This model powerfully predicts human fixations on 749 variations of 108 natural images, achieving 98% of the ROC area of a human-based control, whereas the classical algorithas of Itti & Koch ([2], [3], [4]) achieve only 84%.)
Platform: |
Size: 8948736 |
Author: 佳子 |
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Description: 用python做一个分形图形-koch雪花，非常适合刚学python的新手学习函数的迭代.(Using Python to make a fractal -koch snowflake, it is very suitable for Python learning new iterations.)
Platform: |
Size: 1024 |
Author: lukas233 |
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