Machine learning via fusion of discriminative and mean field models and its application to image recognition

在机器学习中，我们有两种典型的模型，即生成模型和判别模型。我们的目标是将这两种模型结合起来，以获得更详细的机器学习模型。得到两个主要结果如下。首先，设计了一种特殊的判别随机场，并将其应用于高性能视频图像分类。其次，对核随机场进行建模，将其构造为带有核的随机场，并将其应用于场景分类；

In machine learning, we have two typical models, i. e., generative and discriminative models. We aimed to combine both of these models in order to obtain more elaborated machine learning models. Two main results are obtained as follows. Firstly, we designed a special discriminative random field and applied it to high performance video image classification. Secondly, we modeled a kernel random field which is constructed as random field with kernels, and successively applied to scene classification.