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Titlebook: Innovationen und Gewerkschaften; Deutschland — Japan Horst Albach Book 1991 Springer Fachmedien Wiesbaden 1991 Arbeitsbeziehungen.Arbeitsr

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樓主: HEM
21#
發(fā)表于 2025-3-25 04:15:10 | 只看該作者
22#
發(fā)表于 2025-3-25 09:51:26 | 只看該作者
23#
發(fā)表于 2025-3-25 11:55:17 | 只看該作者
24#
發(fā)表于 2025-3-25 16:46:50 | 只看該作者
Tezuka Kazuakif the optic disc, fovea, and blood vessels have became essential level for automated diagnosis practices. In diabetic retinopathy, the fundus regions are normally overbright, faint regional boundary and irregular in shape. Besides, the features of fundus region vary from regular tissues and hence, t
25#
發(fā)表于 2025-3-25 22:28:14 | 只看該作者
26#
發(fā)表于 2025-3-26 02:51:22 | 只看該作者
Takashi Sumi extracting low-level features or mid-level features without enough high-level information. Moreover, these approaches do not take the characteristics (scales) of different emphysema into account, which are crucial for feature extraction. In contrast to previous works, we propose a novel deep learni
27#
發(fā)表于 2025-3-26 07:05:01 | 只看該作者
28#
發(fā)表于 2025-3-26 12:25:22 | 只看該作者
29#
發(fā)表于 2025-3-26 14:01:13 | 只看該作者
Jaakko Honkonces in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems...Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academi
30#
發(fā)表于 2025-3-26 19:48:42 | 只看該作者
ture domain. This chapter introduces a new transfer learning method, called “two-stage feature transfer,” to analyze textural medical images by deep convolutional neural networks. In the process of the two-stage feature transfer learning, the models are successively pre-trained with both natural ima
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