Benchmarking MRI Reconstruction Neural Networks on Large Public Datasets

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The question is about the relevancy of using video on which temporal information can be used to help human annotation to train purely image semantic segmentation pipeline

In Table 2, we report the reconstruction PSNRs obtained using the proposed network, and for a network with the same architecture where the mapping is learned (‘Free Layer’)

Our simulation shows than the proposed recur- rent network improves the reconstruction quality compared to static approaches that reconstruct the video frames inde- pendently..

Table 1: Average peak signal-to-noise ratio (PSNR) and average structural similarity (SSIM) over the UCF-101 test dataset for the three different methods, as the least-squares

The results obtained in the reliability prediction study of the benchmark data show that MLMVN out- performs other machine learning algorithms in terms of prediction precision and

In practice the modulation amplitude is always smaller than this length because one great advantage of a broadband source is the possibility of using objectives with a depth of

Figure 8.6 shows converter efficiency versus modulation frequency when the converter is driven with duty cycles of 20, 50, and 80%, for an input voltage of 14.4 V, and a fixed