A Novel Active Learning Algorithm for Robust Image Classification
A Novel Active Learning Algorithm for Robust Image Classification
复制标题
一种新颖的鲁棒图像分类主动学习算法
DOI：
10.1109/access.2020.2968082
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
Hong Zhenjie
中科院分区：
文献类型：
--
作者：
Xiong Xingliang;Fan Mingyu;Yu Chuang;Hong Zhenjie
Training samples need to be labeled before being used to train classification model, which usually takes too much labor and material resources. Recently, this problem has attracted widespread attention. In order to reduce the workload of labeling samples, we propose a novel active learning methodology, which uses locally linear reconstruction coefficients to construct semi-supervised data manifold adaptive kernel space. Comparing the new method with other sampling approaches on several real-world image datasets, experimental results indicate that the novel algorithm has preferable classification ability. Especially, it can show higher classification accuracy under the condition that only a few samples are selected to train the classifier model.
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