A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
Evelina Lamma, Fabrizio Riguzzi, Andrea Stambazzi,...
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
Kai Guo, Xiaokang Yang, Rui Zhang, Guangtao Zhai, ...
: In this paper we discuss theoretical foundations and a practical realization of a real-time traffic sign detection, tracking and recognition system operating on board of a vehicl...
Andrzej Ruta, Fatih Porikli, Shintaro Watanabe, Yo...
We combine linear discriminant analysis (LDA) and K-means clustering into a coherent framework to adaptively select the most discriminative subspace. We use K-means clustering to ...