Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

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,Werkstoffkennwerte bei zügiger Belastung, integrated circuits, manually labeling large datasets of all kinds of components for training machine learning models is time-consuming and impractical. To address this challenge, we propose a novel one-shot conditional component rotation detection framework, PolarNet. Given a standard image of the

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Linear-elastisches Werkstoffverhalten,a on semi-supervised learning. However, current openset semi-supervised learning approaches directly discard the identified ood data, while ignoring the positive impact of ood data similar to in-distribution (ID) data on semi-supervised learning. And the method based on learnable parameters is prone

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