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We introduce an improved version of the Digital Detector Emulator able to generate programmable analog shapes with a rise time up to 1 ns. This is suitable for all the fast-scintillator emulation environments. Moreover, the output dynamic of 16 bits allows the device to be used in high resolution spectroscopy applications. The instrument is not a pulse generator of recorded shapes but a synthesizer...
The reduced availability of 3He is a motivation for developing alternative neutron detectors. 6Li-enriched CLYC (Cs2LiYCl6), a scintillator, is a promising candidate to replace 3He. The neutron and gamma ray signals from CLYC have different shapes due to the slower decay of neutron pulses. The long decay time associated with the scintillation emission of CLYC often results in pulse pileup for event...
Silicon Photomultipliers (SiPMs) are rapidly developing photosensitive devices which are already used as an alternative to photomultipliers (PMT) in the newly developed calorimeters for high-energy physics. Many measurement results and SIPMs parameters based on signal amplitude histograms analysis have been published. Author presents a special automated system for scanning SIPMs surfaces with a fast...
For a given energy deposited, the Fano factor of a scintillator is defined as the ratio of the variance of the number of scintillation photons to the mean number of scintillation photons. Correlations in time between the signals from two photomultiplier tubes collecting light from the same scintillation event were used to estimate the Fano factor of scintillators. At 662 KeV, LaBr3:Ce was found to...
Mass accountancy measurement is a nuclear nonproliferation application which utilizes coincidence and multiplicity counters to verify special nuclear material declarations. With a well-designed and efficient detector system, several relevant parameters of the material can be verified simultaneously. 6LiF/ZnS scintillating sheets may be used for this purpose due to a combination of high efficiency...
this paper presents a comparison of two different chains, used for the processing of the signal generated by an ionizing particle crossing a detection cell. The results of the two chains are discussed.
Conventional peak detection algorithms are not designed to include information on the expected peak shape. Therefore, commonly used detectors discard this valuable information and do not perform optimally in regard to the given possibilities. Designed and evaluated is a detector based on an artificial neural network, which is employed for pattern recognition in order to exploit the peak shape information...
Research in traffic light recognition (TLR) has stagnated compared to related computer vision areas, such as pedestrian detection and and traffic sign recognition. We focus on the detection sub-problem, since this is the most challenging problem and solving this is the key to a successful TLR system. This is done by looking at four detectors from different author groups and their reported results...
Color represents an important attribute in the field of traffic sign recognition. However, when the color of the traffic sign fades or the traffic scene is collected in gray as in the case of Infrared imaging, then color based recognition systems fail. Other problems related to color are simply that different countries use different colors. Even within the European Union, colors of traffic signs are...
Indoor localization techniques can produce significant errors in non-line-of-sight (NLOS) channels. To mitigate this problem, a new approach to channel identification based on the ratio of the minimum slope and skewness of the output of an energy detector is presented. The IEEE 802.15.3c 60 GHz channel models are used to examine the performance of this technique. The simplicity of the proposed approach...
The goal of this work is to recover road networks from aerial images. This problem is extremely challenging because roads not only exhibit a highly varying appearance but also are usually occluded by nearby objects. Most importantly, roads are complex structures as they form connected networks of segments with slowly changing width and curvature. As an effective tool for their extraction, we propose...
Object class detection has been a synonym for 2D bounding box localization for the longest time, fueled by the success of powerful statistical learning techniques, combined with robust image representations. Only recently, there has been a growing interest in revisiting the promise of computer vision from the early days: to precisely delineate the contents of a visual scene, object by object, in 3D...
We propose a facial landmarks detector, in which a part-based model is incorporated with holistic face information. In the part-based model, the face is modeled by the appearance of different face parts and their geometric relation. The appearance is described by pixel normalized difference descriptor. This descriptor is the lowest computational complexity as compared with existing state-of-the-art...
This paper describes a novel approach for generating object proposals for ball detection. Our method, called shape detector, captures the possible contours of balls and then transfers them into proposal bounding boxes which may contain the target object. These proposal bounding boxes can be further used in class-specific object detection task. Our experiment results on part of ILSVRC dataset show...
We consider the requirements of cognitive radar detection in the presence of non-Gaussian clutter. A pair of machine learning approaches based on non-linear transformations of order statistics are examined with the goal of adaptively determining the optimal detection threshold within the low sample support regime. The impact of these algorithms on false alarm rate is also considered. It is demonstrated...
If we compare the object recognition abilities of human and computer-based system, it is much complex task for a machine. Human brain can recognize an object quickly but for a computer system accuracy depends on the level of algorithms, software and tools used for recognition. Image processing, pattern recognition and compute vision are being challenging but becomes a crucial component for developing...
This paper describes the method of the Digital pulse processing with a series of algorithms. Digital pulse processing is a signal processing technique in which detector (preamplifier output) signals are directly digitized and processed to extract quantities of interest. Our algorithm is designed for the realization of digitally determining the basic pulse parameters and tackling the problem of pulse...
We present an audiovisual approach to the problem of voice activity detection for systems with a single microphone and a single camera with multiple people in the camera's field of view. We aim to have a speech activity detection result per person. The approach utilizes a face tracking and lip contour tracking algorithm for the video analysis, and pitch presence detection and formant frequency tracking...
We present a double-parameter CFAR with very reasonable losses and low computational complexity. Its basic architecture has been conceived from tail extrapolation theory. The detector uses a detection threshold, set from the measured PFA which is obtained with an auxiliary threshold (pseudothreshold), lower than the final detection threshold. Starting from the basic scheme, a CFAR detector for Weibull...
We propose a machine learning-based method to automatically detect flow diverters in cerebral C-arm CT images. An appearance detector is learned to generate hypotheses of a flow diverter's location in a volumetric image. A probabilistic framework incorporating a local appearance and shape model is developed to trace the flow diverter. Promising results have been obtained on clinical data. The proposed...
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