The Video National Imagery Interpretability Rating Standard (V-NIIRS) consists of a ranked set of subjective criteria to assist analysts in assigning an interpretability quality level to a motion imagery clip. The V-NIIRS rating standard is needed to support the tasking, retrieval, and exploitation of motion imagery. A criteria survey was conducted to yield individual pair-wise criteria rankings and scores. Statistical analysis shows good agreement with expectations across the 9-levels of interpretability, for each of the 7 content domains.
A: Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays. K : Computerized Tomography (CT) and Computed Radiography (CR); Plasma diagnostics -interferometry, spectroscopy and imaging 1Corresponding author. 2See the author list of Overview of the JET preparation for Deuterium-Tritium Operation by E. Joffrin et al. in Nucl.
A perceptual evaluation compared tracking performance when using color versus panchromatic synthetic imagery at low frame rates. Frame rate was found to have an effect on tracking performance for the panchromatic motion imagery. Color was found to be associated with improved tracking performance at 2 frames per second (FPS), but not at 6 FPS or greater. A self estimate of task confidence given by the respondents was found to be correlated to the measured tracking performance, which supports the use of task confidence as a proxy for task performance in the future development and validation of a motion imagery rating scale.
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