2016
Learning to Select Pre-Trained Deep Representations With Bayesian Evidence Framework
CVPR 2016oral
We propose a Bayesian evidence framework to facilitate transfer learning from pre-trained deep convolutional neural networks (CNNs). Our framework is formulated on top of a least squares SVM (LS-SVM) classifier, which is simple and fast in both training and testing, and achieves competitive performa…