Direct readability is one advantage of superheated droplet detectors in neutron dosimetry. Utilizing such a distinct characteristic, an imaging readout system analyzes image of the detector for neutron dose readout. To improve the accuracy and precision of algorithms in the imaging readout system, machine learning algorithms were developed. Deep learning neural network and support vector machine algorithms are applied and compared with generally used Hough transform and curvature analysis methods. The machine learning methods showed a much higher accuracy and better precision in recognizing circular gas bubbles
With the utilization of machine learning, computers have been able to efficiently classify data. Dee...
High gamma backgrounds can pose a significant source of interference in solid-state neutron detector...
International audiencePulse shape discrimination algorithms have been commonly implemented on embedd...
Alternative slow neutron detection technologies are desired in response to needs by homeland securit...
The main focus of this work is to use machine learning and data mining techniques to address some ch...
In neutron transmission spectroscopic imaging, the transmission spectrum of each pixel on a two-dime...
A new Machine Learning algorithm for shower-head identification in the NeuLAND neutron detector is p...
In neutron transmission spectroscopic imaging, the transmission spectrum of each pixel on a two-dime...
International audienceOrganic scintillators are widely used for neutron/gamma detection. Pulse shape...
LDMX is a fixed target experiment designed to search for light dark matter. The experiment will sear...
Recently, learning algorithms such as Convolutional Neural Networks have been successfully applied i...
In this paper, Machine learning techniques have been employed for preparation and estimation of 96 M...
Coded Aperture γ-cameras have been used for more than three decades for imaging radioactive source d...
The safe operation of nuclear power plants is highly dependent on the ability of quickly and accurat...
The safe operation of nuclear power plants is highly dependent on the ability of quickly and accurat...
With the utilization of machine learning, computers have been able to efficiently classify data. Dee...
High gamma backgrounds can pose a significant source of interference in solid-state neutron detector...
International audiencePulse shape discrimination algorithms have been commonly implemented on embedd...
Alternative slow neutron detection technologies are desired in response to needs by homeland securit...
The main focus of this work is to use machine learning and data mining techniques to address some ch...
In neutron transmission spectroscopic imaging, the transmission spectrum of each pixel on a two-dime...
A new Machine Learning algorithm for shower-head identification in the NeuLAND neutron detector is p...
In neutron transmission spectroscopic imaging, the transmission spectrum of each pixel on a two-dime...
International audienceOrganic scintillators are widely used for neutron/gamma detection. Pulse shape...
LDMX is a fixed target experiment designed to search for light dark matter. The experiment will sear...
Recently, learning algorithms such as Convolutional Neural Networks have been successfully applied i...
In this paper, Machine learning techniques have been employed for preparation and estimation of 96 M...
Coded Aperture γ-cameras have been used for more than three decades for imaging radioactive source d...
The safe operation of nuclear power plants is highly dependent on the ability of quickly and accurat...
The safe operation of nuclear power plants is highly dependent on the ability of quickly and accurat...
With the utilization of machine learning, computers have been able to efficiently classify data. Dee...
High gamma backgrounds can pose a significant source of interference in solid-state neutron detector...
International audiencePulse shape discrimination algorithms have been commonly implemented on embedd...