In this paper, we discuss the problem of using semi-supervised learning method to do video semantic annotation.
本文讨论了利用半监督学习方法进行视频语义标注的问题。
Therefore, this algorithm has solved the problem of model updating in semi-supervised learning under appropriate conditions.
该算法在一定条件下解决了半监督学习环境下的模型更新问题。
So, the semi-supervised learning method by learning a small number of labeling samples and a large number of samples to establish classifier came into being.
如此，通过对少量已标记样本和大量未标记的样本进行学习从而建立分类器的半监督学习方法应运而生。
The comparison and analysis of geometric information's impact on semi-supervised learning is performed through the experiments.
最后通过实验对比和分析了几种几何信息对半监督学习效果的影响。
The ANN can derive a continuous-spread stability index to indicate the relative stability degree by means of a semi-supervised learning algorithm.
使用一个半监督学习算法，ANN可产生一个能够指示相对稳定度的连续分布的暂态稳定指标。
If the ultimate effect of the semi-supervised method is the same or close to the result of supervised learning method, the semi-supervised learning is more advantages in labor costs and achievement.
若其最终的学习效果与全监督学习方法的效果一致或接近，则在人工成本和实现上，半监督学习方法更具有优越性。
Semi-Supervised Learning : Input data is a mixture of labelled and unlabelled examples.
半监督学习：输入数据由带标记的和不带标记的组成。
Semi-supervised learning algorithms, which consider both labeled and unlabeled data, can improve learning effectiveness significantly.
半监督学习算法同时考虑有标记和无标记数据，能显著提升学习效果。
Semi-supervised learning methods including self-training and co-training were shown in the task of PPI on how to alleviate the tag burden as much as possible.
使用半监督学习方法中的自训练、协同训练方法，利用少量已标注样本和大量未标注样本来完成蛋白质关系抽取的任务。
Semi-supervised learning methods including self-training and co-training were shown in the task of PPI on how to alleviate the tag burden as much as possible.
使用半监督学习方法中的自训练、协同训练方法，利用少量已标注样本和大量未标注样本来完成蛋白质关系抽取的任务。
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