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Titlebook: Makro?konomik; Theorie, Empirie und Uwe Westphal Textbook 1994Latest edition Springer-Verlag Heidelberg 1994 Arbeitsmarkt.Geld.Geldmenge.Ge

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51#
發(fā)表于 2025-3-30 11:18:34 | 只看該作者
52#
發(fā)表于 2025-3-30 14:49:02 | 只看該作者
Uwe Westphalative (ADNI), and conduct some experiments to evaluate their effect in two tasks of AD diagnosis, including AD identification and mild cognitive impairment (MCI) conversion prediction. Experimental results demonstrate that our UDA strategy is effective to learn a reliable mapping to high-quality MR
53#
發(fā)表于 2025-3-30 17:38:48 | 只看該作者
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發(fā)表于 2025-3-30 23:36:00 | 只看該作者
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發(fā)表于 2025-3-31 04:31:53 | 只看該作者
Uwe Westphalzation in training deep networks. In our empirical study, we use MRI-based brain regional measurements as features to conduct the CN vs MCI and AD vs MCI binary classifications. We compare the balanced accuracy of our model with other machine learning models and deep neural network loss functions th
56#
發(fā)表于 2025-3-31 05:02:04 | 只看該作者
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發(fā)表于 2025-3-31 15:18:57 | 只看該作者
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發(fā)表于 2025-3-31 19:22:00 | 只看該作者
60#
發(fā)表于 2025-3-31 23:21:40 | 只看該作者
Uwe Westphal adversarial term. The adversarial term adopts a generator called Residual Attention U-Net (., RAU-Net) to produce the probability maps that cannot be distinguished by the ground-truth. Based on the adversarial model, we can simultaneously estimate the probabilities of many pixels with high-order co
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