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Titlebook: Hip Magnetic Resonance Imaging; Young-Jo Kim,Tallal Charles Mamisch Book 2014 Springer Science+Business Media, LLC 2014 Hip.MRI.Orthopedic

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樓主: Interjection
21#
發(fā)表于 2025-3-25 03:21:17 | 只看該作者
ractical settings. Yet, especially for sensible domains such as FR we expect algorithms to work equally well for everyone, regardless of somebody’s age, gender, skin colour and/or origin. In this paper, we investigate a methodology to quantify the amount of bias in a trained Convolutional Neural Net
22#
發(fā)表于 2025-3-25 08:46:32 | 只看該作者
23#
發(fā)表于 2025-3-25 15:24:16 | 只看該作者
Stephan Domayer MD, PhD,Sebastian Apprich MD,Benjamin Schmitt MD,Oliver Bieri PhD,Siegfried Trattnigate of the art models such as LSTM and Transformer are trained by backpropagation of losses into prior hidden states and inputs held in memory. This allows gradients to travel through time from present to past and effectively learn with perfect hindsight, but at a significant memory cost. In this pa
24#
發(fā)表于 2025-3-25 17:49:37 | 只看該作者
25#
發(fā)表于 2025-3-25 19:59:52 | 只看該作者
26#
發(fā)表于 2025-3-26 01:17:37 | 只看該作者
rried out. In the proposed method, the conventional back propagation (BP) learning algorithm is used to train the network by minimizing the representation error. A new pruning algorithm employing statistical analysis can quantify the importance of each hidden unit. This is accomplished by providing
27#
發(fā)表于 2025-3-26 06:42:48 | 只看該作者
Sarah D. Bixby MDtext corpus and are meant to serve state-of-the-art results over tasks like text classification. In this work, we conduct a comparative study between monolingual and multilingual BERT models. We focus on the Marathi language and evaluate the models on the datasets for hate speech detection, sentimen
28#
發(fā)表于 2025-3-26 11:50:43 | 只看該作者
Bernd Bittersohl MD,Christoph Zilkens MDic decision-making through the ability to recognise patterns in medical images. Such technologies started showing promising results in their ability to match or outperform physicians in certain specialities and improve the quality of medical diagnosis. Convolutional neural networks are one state-of-
29#
發(fā)表于 2025-3-26 14:31:02 | 只看該作者
Nancy A. Chauvin MD,Diego Jaramillo MD, MPHoncerns that this increasing popularity has exacerbated issues of unfairness and discrimination toward individuals. Researchers in this field have proposed a wide variety of fairness-enhanced classifiers and fairness matrices to address these issues, but very few fairness techniques have been transl
30#
發(fā)表于 2025-3-26 18:27:00 | 只看該作者
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