This paper proposes a visual words ambiguity analysis method based on text categorization. The codebook is generated by the BOW model.
为解决该问题，提出一种基于文本分类的视觉单词歧义性分析方法。
A new method of describing and matching spatial context is proposed to effectively improve the distinguishability of objects in visual words-based image retrieval.
提出了一种空间上下文描述与匹配方法，有效地提高了基于视觉关键词的图像检索中目标对象的可区分性。
We propose a novel kernel which fuses multi-level contexts of visual words.
基于普通的视觉单词，提出了一种新的能够融合单词多层上下文的核函数。
When you hear words like "see, appears, looks," or phrases like "picture this, looks clear, bright future," these are all visual words.
当你听到像“看见、看着、出现”这些词，或像“画出来、看上去清楚、看上去明亮、看上去蛮远”等短语，都是视觉型的词语。
When you hear words like "see, appears, looks," or phrases like "picture this, looks clear, bright future," these are all visual words.
当你听到像“看见、看着、出现”这些词，或像“画出来、看上去清楚、看上去明亮、看上去蛮远”等短语，都是视觉型的词语。
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