Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
In this paper, we propose a new vector quantization method to create video thumbnail. In particular, we employ video time density function (VTDF) to explore the temporal character...
- We previously proposed a Colored Petri Net (CPN) based modeling methodology to model multiagent systems. The methodology creates a component to describe the local behavior for ea...
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
Abstract. We present a method for learning feature descriptors using multiple images, motivated by the problems of mobile robot navigation and localization. The technique uses the ...
Jason Meltzer, Ming-Hsuan Yang, Rakesh Gupta, Stef...