Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-...
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...
Multi-label learning refers to the problems where an instance can be assigned to more than one category. In this paper, we present a novel Semi-supervised algorithm for Multi-labe...
Gang Chen, Yangqiu Song, Fei Wang, Changshui Zhang
— Constrained clustering (semi-supervised learning) techniques have attracted more attention in recent years. However, the commonly used constraints are restricted to the instanc...
There has been much work on applying multiple-instance (MI) learning to contentbased image retrieval (CBIR) where the goal is to rank all images in a known repository using a smal...