Most of the current successes of deep transfer learning-based fault diagnosis require two
assumptions: 1) the health state set of source machines should overlap that of target …

This paper investigates recent research on active learning for (geo) text and image
classification, with an emphasis on methods that combine visual analytics and/or deep …

Retinal disease classification is a significant problem in computer-aided diagnosis (CAD) for
medical applications. This paper is focused on a 4-class classification problem to …

Many statistical learning models hold an assumption that the training data and the future
unlabeled data are drawn from the same distribution. However, this assumption is difficult to …

Abstract Knowledge in the source domain can be used in transfer learning to help train and
classification tasks within the target domain with fewer available data sets. Therefore, given …

With the deepening of transfer learning research, researchers are no longer satisfied with
the classification of knowledge in a single field but hope that the classification of knowledge …

With the always increasing amount of image data, it has become a necessity to automatically
look for and process information in these images. As fashion is captured in images, the …

With rapid growth of digital publishing, a great deal of document datum has been published
online for a widely spread of knowledge innovations, which is an important resource for …

In this paper, we propose an emotion separated method (SeTF· IDF) to assign the emotion
labels of sentences with different values, which has a better visual effect compared with the …

E-commerce has changed the way people shop and unleashed new levels of demand for
goods by making it easier to buy and deliver goods to customers. There are now more …