We present a simple framework to model contextual
relationships between visual concepts. The new framework
combines ideas from previous object-centric methods
(which model conte...
Nikhil Rasiwasia (University Of California, San Di...
We propose a new method to partition an unlabeled dataset, called Discriminative Context Partitioning (DCP). It is motivated by the idea of splitting the dataset based only on how...
A recent report by the National Research Council (NRC) declares neural networks “hold the most promise for providing powerful learning models”. While some researchers have expe...
Amy E. Henninger, Avelino J. Gonzalez, Michael Geo...
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
— A novel framework to context modeling, based on the probability of co-occurrence of objects and scenes is proposed. The modeling is quite simple, and builds upon the availabili...