*.zip
This dataset contains the trained model that accompanies the publication of the same name:
Anup Tuladhar*, Serena Schimert*, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert, "Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks," in IEEE Access, vol. 8, pp. 94871-94879, 2020, doi:10.1109/ACCESS.2020.2995632. *: Co-first authors
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Objective: No data currently exist on the reproducibility of photographic food records compared to diet diaries, two commonly used methods to measure habitual dietary intake. Our aim was to examine the reproducibility of diet diaries, photographic food records, and a novel electronic sensor, consisting of counts of chews and swallows using wearable sensors and video analysis, for estimating energy intake.
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2D geometrically shaped constellations that are simultaneously robust to both residual phase noise and AWGN (GS-RPN) for 8, 16, 32 and 64-ary formats. The presented formats are optimised at the generalised mutual information (GMI) threshold of 0.96m bits/symbol, where m is the number of bits per symbol. Additionally, we added AWGN-only constellations (GS-AWGN) to serve as a reference.
Note: This is a supplementary dataset for a journal submission.
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test
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PS_DISP is a trial bundled script written on bash shell and Matlab code. The script requires Generic Mapping Tools (GMT) and Matlab Software and runs under Linux operating system. The purpose of PS DISP is to generate 2D or 3D vectors displacement from InSAR both ascending and descending orbit either from the mean velocity or time-series data. The 1.5 beta version includes the computation of the 3D field using an optimized approach with variance component estimation (VCE).
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This is source code for the paper "Analog Self-Interference Cancellation Using Auxiliary Transmitter Considering IQ Imbalance and Amplifier Nonlinearity" submitted to IEEE Transactions on Wireless Communications.
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