Segmentation of nasopharyngeal carcinoma (NPC) from computed tomography (CT) image
is conducive to the clinical healthcare. Nevertheless, due to the large shape variations …

Semi-supervised text classification (SSTC) aims at text classification with few labeled data
and massive unlabeled data. Recent works achieve this task by pseudo-labeling methods …

Web 2.0 helped user-generated platforms to spread widely. Unfortunately, it also allowed for
cyberbullying to spread. Cyberbullying has negative effects that could lead to cases of …

Online target maneuver recognition is an important prerequisite for air combat situation
recognition and maneuver decision-making. Conventional target maneuver recognition …

Hierarchical classification identifies a sample from the root node to a leaf node along the
hierarchical structures of labels. It is often difficult to perform leaf-node prediction owing to …

Automatic segmentation of medical images is a necessary prerequisite for diagnosing
related diseases. Magnetic resonance imaging (MRI) is a widely used non-invasive method …

Remote sensing scene classification plays a critical role in a wide range of real-world
applications. Technically, however, scene classification is an extremely challenging task due …

Electroencephalography (EEG) is an objective tool for emotion recognition and shows
promising performance. However, the label scarcity problem is a main challenge in this field …

Self-training is a commonly semi-supervised learning Algorithm framework. How to select
the high-confidence samples is a crucial step for algorithms based on self-training …

As a powerful tool for data streams processing, the vast majority of existing evolving
intelligent systems (EISs) learn prediction models from data in a supervised manner …