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by
Xie, Junyuan, author.
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Transfer Learning with Deep Neural Networks for Computer Vision / Xie, Junyuan, author.
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Davis, John McDonald Cameron, author.
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Communication concepts and their implementation in computer networks / Davis, John McDonald Cameron
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Ahmad, Ayesha, author.
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convolutional neural networks (CNNs), which are very successful in extracting features from the data. However
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Almada, Demetrius J., author.
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-Wave quantum computer. As a result, we found that temperature chaos must be caused by structures deeper than
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Peng, Xi, author.
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learning and computer vision. Over the last decade, deep neural networks have achieved remarkable success
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Wen, Haiguang, author.
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whether neuroscience theory can be applied to artificial models to advance computer vision. To address
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Wang, Haiyan, author.
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algorithms, various machine learning algorithms including deep neural networks, and optimal state estimator
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Konakas, Spiridon, author.
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areas of computer graphics and computer networks are discussed. The six chapters of the thesis include
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Ma, Christopher, author.
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regulation models of proteins in biology, communities of people within social network. Since complex networks
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Kim, Jinseok, author.
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the statistical properties of coauthorship networks constructed from algorithmically disambiguated
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Keshavarzi, Parviz, author.
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computer networks. This thesis describes high performance techniques which speed up the modular
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Jadhav, Shrikant Shridhar, author.
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, e.g., computer vision [10], cellular networks [53] and deep neural network [26]. In our experiments

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