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Titlebook: Industrial Democracy in the Chinese Aerospace Industry; The Innovation Catal Denise Tsang Book 2017 The Editor(s) (if applicable) and The A

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楼主: SORB
发表于 2025-3-23 13:15:55 | 显示全部楼层
Denise TsangExplores one of the key factors driving the fast expanding Chinese aerospace industry.Discusses the future prospects and implications of the system within a global economy.Compares and contrasts the C
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978-1-349-84562-0The Editor(s) (if applicable) and The Author(s) 2017
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Denise Tsangative impact of noisy image labels, and is beneficial to train a high performance CNN based classifier. Besides, we released a fine-grained product dataset called AliProducts, which contains more than 2.5 million noisy web images crawled from the internet by using queries generated from 50,000 fine-
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Denise Tsangns and is hence substantially more efficient than the NS iteration using matrix-matrix multiplications. Moreover, RUN readily supports the normalization on compact bilinear features from TS or RM. Besides, RUN is simpler than the NS iteration and easier for implementation in practice. As RUN is a di
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Denise Tsangthe entire dataset. We learn a feature center for each category and realize the global feature consistency by forcing the object features to approach class-specific centers. The global centers are actively updated with the training process. The two constraints can benefit each other to learn consist
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Denise Tsangmay cause the under-fitting problem, resulting in a less effective model. To reduce the dependency of BN on batch size, we propose a momentum BN (MBN) scheme by averaging the mean and variance of current mini-batch with the historical means and variances. With a dynamic momentum parameter, we can au
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