Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
common features in all learning objects only. The In this paper, we propose two methods of clustering learning images to generate prototypes automatically for object recognition. O...
This paper presents a probabilistic grammar approach to the recognition of complex events in videos. Firstly, based on the original motion features, a rule induction algorithm is a...
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Related objects may look similar at low-resolutions; differences begin to emerge naturally as the resolution is increased. By learning across multiple resolutions of input, knowle...