OALib Journal期刊
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?利用图像类标信息的自调式字典学习方法
DOI: 10.13232/j.cnki.jnju.2015.02.016, PP. 320-327
Keywords: 类标签,自调学习,字典学习
Abstract:
?字典学习是图像分类的关键研究问题之一.现有的字典学习方法大都假设所有训练样本同等重要.实际上,训练样本由于样本之间关联性作为一种“隐藏属性”是未知的,因此,训练样本的学习顺序也与学习效果密切相关.提出一种将自调学习机制融合于字典更新过程的新型字典学习方法,在字典学习中,学习的过程并不是一次处理所有训练样例,而是从简单的训练样例学起,通过迭代逐步扩展至整个训练数据集.针对自调式过程是一种无监督式的学习这一特点,融合类标机制,利用图像类标信息进行监督,得到一种更加高效的简单样本判别方法,从而提高学习过程中反复迭代的效率.在caltech-101数据集上进行图像分类实验,并和其他几种字典学习算法进行了分析和比较,结果表明本文算法在字典表示以及分类效果上都取得了更好的效果.
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