In this paper we present an adaptive but robust object
detector for static cameras by introducing classifier grids.
Instead of using a sliding window for object detection we
pro...
Peter M. Roth, Sabine Sternig, Helmut Grabner, Hor...
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...
The Distributed Shared Memory (DSM) model is designed to leverage the ease of programming of the shared memory paradigm, while enabling the highperformance by expressing locality ...
We apply statistical relational learning to a database of criminal and terrorist activity to predict attributes and event outcomes. The database stems from a collection of news ar...
B. Delaney, Andrew S. Fast, W. M. Campbell, C. J. ...