This paper describes a prototype design and implementation of a real-time (on-line) knowledge generation component which can be utilised in industrial Supervisory Control and Data Acquisition (SCADA) systems. The over...
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Researchers, teachers, librarians, and individuals in daily practice perform various activities that require the processing of large amounts of knowledge and dynamic information flow. The database application BIKE (Ba...
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Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs...
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Design of a novel varifocal freeform optics with aspheric surface profiles to reduce aberration effects. Its focal length will be tuned by rotating one of two helically formed lens bodies around the optical axis. ...
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Data augmentation methods for neural machine translation are particularly useful when limited amount of training data is available, which is often the case when dealing with low-resource languages. We introduce a nove...
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In this paper, we present a method for the automated determination of aerosol jet parameters for the Aerosol-on-Demand (AoD) jet-printhead. A critical aspect in the simulation of our computational fluid dynamics (CFD)...
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An important point for the widespread dissemination of FAIR-data is the lowest possible entry barrier for preparing and providing data to other scientists according to the FAIR criteria. If scientists have to manually...
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The article shows possibilities of obtaining anthropometrical data through the image analysis-image processing. In our case, the subject of the analysis is a specific human image focused on the unique contours of the ...
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Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron *** study the powder samples that are widely used in materials development,scanning electron micro...
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Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron *** study the powder samples that are widely used in materials development,scanning electron microscopes(SEMs)are increasingly used at the laboratory scale to generate large datasets with hundreds of *** these images to identify distinct particles and determine their morphology requires careful analysis,and automating this process remains *** this work,we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM *** address several challenges inherent to measurements,such as image blur and particle ***,our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a *** that disparate length scales are often present in large datasets,we use this framework to create two models that are separately trained to handle images obtained at low or high *** testing these models on a variety of inorganic samples,our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts,revealing comparable accuracy while requiring a fraction of the *** findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.
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