In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
This paper proposes a new background subtraction method for detecting moving objects from a time-varied background. While background subtraction has traditionally worked well for ...
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Traditionally, software engineering processes are based on a formalist model that emphasizes strict documentation, procedural and validation standards. Although this is a poor fit...
Evolutionary models typically rely on a single level of evolution for training a team of cooperating agents. I present a model that evolves at two levels—an “organizational”...