We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
Moving object databases (MOD) have gained much interest in recent years due to the advances in mobile communications and positioning technologies. Study of MOD can reveal useful i...
Roman Yarovoy, Francesco Bonchi, Laks V. S. Lakshm...
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
We describe a recommender system based on Dynamically Structured Holographic Memory (DSHM), a cognitive model of associative memory that uses holographic reduced representations a...
Matthew Rutledge-Taylor, Andre Vellino, Robert L. ...
Abstract. Active Learning methods rely on static strategies for sampling unlabeled point(s). These strategies range from uncertainty sampling and density estimation to multi-factor...