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A method is described to automatically generate spectrum reference data for radioisotope identification devices respecting a detectors physical individuality. It extracts the peak shape and non-proportionality characteristics of scintillation and CZT detectors. The representation of these quantities is done with evolutionary ensembles, groups of N-dimensional autonomous points, which are propagated...
Neutron/Gamma pulse shape discrimination (PSD) was measured using stilbene and EJ-299-34 plastic scintillators with readout by silicon photomultipliers (SiPMs). The SiPM pulses were digitized and processed for energy and pulse shape information using a digital technique performing numerical weighted integrations on each pulse. A genetic algorithm (GA) was developed to optimize the weighting vectors...
Traditional gamma camera collimators have been based on a standard parallel design, usually with parallel holes. The collimator determines the resolution of the camera, but is also the determining factor of the number of counts detected. The uncertainty about the origin of the detected photons is modelled by a Point Spread Function (PSF), which, in literature, is normally assumed to be a Gaussian...
In object detection, the goals of successfully discriminating between different kinds of objects (object classification) and accurately identifying the positions of all objects of interest in a large image (object localisation) are potentially in conflict. We propose a Multi-Objective Genetic Programming (MOGP) approach to the task of providing a decision-maker with a diverse set of alternative object...
The detector generation algorithm is the core of a negative selection algorithm (NSA). In most previous work, the NSAs generate the detector set randomly, which cannot guarantee to obtain an efficient detector set. To generate an approximately optimal detector set, in this paper, a novel detector generation algorithm for the real-valued negative selection algorithm (RNSA) is proposed. The proposed...
This work provides an effective approach based on adaptive neuro-fuzzy inference system to the solution of constant false alarm rate (CFAR) detection for Weibull clutter statistics. The optimal detection thresholds of the ML-CFAR (maximum-likelihood CFAR) detector in Weibull clutter with unknown shape parameter are obtained using fuzzy-neural networks (FNN) technique. The genetic learning algorithm...
The use of genetic algorithms (GAs) tool for the solution of constant false alarm rate (CFAR) detection for Weibull clutter statistics is considered. An approximate expression of the probability of detection (PD) of the ordered statistics (OS)-CFAR detector in Weibull clutter is derived. Optimal threshold values of distributed maximum likelihood (ML)-CFAR detector and distributed OS-CFAR detector...
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