Lisa Ann Osadciw

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This paper presents an evolutionary approach to the sensor management of a biometric security system that improves robustness. Multiple biometrics are fused at the decision level to support a system that can meet more challenging and varying accuracy requirements as well as address user needs such as ease of use and universality better than a single(More)
This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. In the new algorithm, each particle is attracted towards the best previous positions visited by its neighbors, in addition to the other aspects of particle dynamics in PSO. This(More)
A new particle swarm optimization (PSO) algorithm that is more effective for discrete, multi-valued optimization problems is presented. The new algorithm is probabilistically driven since it uses probabilistic transition rules to move from one discrete value to another in the search for an optimum solution. Properties of the binary discrete particle swarms(More)
Sensors have varied constraints, which makes the network challenging for communicating with its peers. In this paper, an extension to the security of physical layer of a predictive sensor network model using the ant system is proposed. The Denial of Service (DoS) attack on sensor networks not only diminishes the network performance but also affects the(More)
This paper presents a Swarm Intelligence based approach for sensor management of a multi sensor networks. Alternate sensor configurations and fusion strategies are evaluated by swarm agents, and an optimum configuration and fusion strategy evolves. An evolutionary algorithm, particle swarm optimization, is modified to optimize two objectives: accuracy and(More)
This paper discusses a multimodal biometric sensor fusion approach for controlling building access. The motivation behind using multimodal biometrics is to improve universality and accuracy of the system. A Bayesian framework is implemented to fuse the decisions received from multiple biometric sensors. The system’s accuracy improves for a subset of(More)
This paper proposes to use Contourlet transform for image compression and feature extraction for wireless face recognition system. The properties of face images and face recognition techniques are incorporated into the design of wireless transmission for such a system. The reasons for utilizing contourlet transform are two-folded. Firstly, in face(More)
Both experimental and theoretical studies have proved that classifier fusion can be effective in improving overall classification performance. Classifier fusion can be performed on either score (raw classifier outputs) level or decision level. While tremendous research interests have been on score-level fusion, research work for decision-level fusion is(More)