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The use of fast pixelated detectors and direct electron detection technology is revolutionising many aspects of scanning transmission electron microscopy (STEM). The widespread adoption of these new technologies is impeded by the technical…
The maintenance, archiving and usage of the design drawings is cumbersome in physical form in different industries for longer period. It is hard to extract information by simple scanning of drawing sheets. Converting them to their digital…
Since local feature detection has been one of the most active research areas in computer vision, a large number of detectors have been proposed. This has rendered the task of characterizing the performance of various feature detection…
Organic scintillators are widely used for fast neutron detection and spectroscopy. Several effects complicate the interpretation of results from detectors based upon these materials. First, fast neutrons will often leave a detector before…
Ptychography is a computational imaging technique that has risen in popularity in the x-ray and electron microscopy communities in the past half decade. One of the reasons for this success is the development of new high performance electron…
Scanning transmission electron microscopy (STEM) has a broad range of applications in materials characterization, including real-space imaging, spectroscopy, and diffraction, at length scales from the micron to sub-{\AA}ngstr\"om. The…
Nuclear physics experiments are always in need of more and more advanced detection systems. During the last years relevant technological developments have come out with many improvements in terms of performance and compactness of detector…
Machine learning is attracting surging interest across nearly all scientific areas by enabling the analysis of large datasets and the extraction of scientific information from incomplete data. Data-driven science is rapidly growing,…
In computational imaging, hardware for signal sampling and software for object reconstruction are designed in tandem for improved capability. Examples of such systems include computed tomography (CT), magnetic resonance imaging (MRI), and…
The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a…
Scientific experiments rely on some type of measurements that provides the required data to extract aimed information or conclusions. Data production and analysis are therefore essential components at the heart of any scientific…
Avalanche photodiodes are commonly used as detectors for low energy x-rays. In this work we report on a fitting technique used to account for different detector responses resulting from photo absorption in the various APD layers. The use of…
In order to take full advantage of the U.S. Department of Energy's billion-dollar investments into the next-generation research infrastructure (e.g., exascale, light sources, colliders), advances are required not only in detector technology…
In the scanning transmission electron microscope, both phase imaging of beam-sensitive materials and characterisation of a material's functional properties using in-situ experiments are becoming more widely available. As the practicable…
In this work, a pattern recognition algorithm was developed to process and analyze electron emission micrographs. Various examples of dc and rf emission are given that demonstrate this algorithm applicability to determine emitters spatial…
Compact direct electron detectors are becoming increasingly popular in electron microscopy applications including electron backscatter diffraction, as they offer an opportunity for low cost and accessible microstructural analysis. In this…
Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…
Recent advances in image data processing through machine learning and especially deep neural networks (DNNs) allow for new optimization and performance-enhancement schemes for radiation detectors and imaging hardware through data-endowed…
A common way of speeding up powder diffraction measurements is the use of one or two dimensional detectors. This usually goes along with worse resolution and asymmetric peak profiles. In this work the influence of a straight linear detector…
Image distortion classification and detection is an important task in many applications. For example when compressing images, if we know the exact location of the distortion, then it is possible to re-compress images by adjusting the local…