We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Abstract— We describe a model for planar distributed assembly, in which agents move randomly and independently on a twodimensional grid, joining square blocks together to form a ...
This paper presents quantitative comparison of the performance of different methods for selecting the guide particle for multi-objective particle swarm optimization (MOPSO). Two p...
David Ireland, Andrew Lewis, Sanaz Mostaghim, Junw...
In this paper we propose a novel framework for efficiently extracting foreground objects in so called shortbaseline image sequences. We apply the obtained segmentation to improve...
Abstract— An optimization algorithm for finding user allocation, bit and power loading in the downlink of MIMO-OFDM systems is proposed. The algorithm represents a generalizatio...
— Particle swarm optimization (PSO) is a stochastic global optimization algorithm inspired by social behavior of bird flocking in search for food, which is a simple but powerful...
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
New video codink standards such as H.264 offer the flexibility to select from a number of reference frames for motion-estimation for a given predicted frame. In this paper, we pro...
In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of pose estimation of a known object. We present a framework tha...
We present a new adaptive algorithm for automatic detection of text from a natural scene. The initial cues of text regions are first detected from the captured image/video. An ada...