Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-...
Many traditional methods for shape classification involve
establishing point correspondences between shapes to
produce matching scores, which are in turn used as similarity
meas...
Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to...
Structured outputs such as multidimensional vectors or graphs are frequently encountered in real world pattern recognition applications such as computer vision, natural language pr...