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Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning
While convolutional neural networks (CNNs) have achieved remarkable performance on various supervised and unsupervised learning tasks, they typically consist of a massive number of parameters. This results in significant memory...
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GIFSL - grafting based improved few-shot learning

A few-shot learning model generally consists of a feature extraction network and a classification module. In this paper, we propose an approach to improve few-shot image classification performance by increasing the...

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Acceleration of Deep Convolutional Neural Networks Using Adaptive Filter Pruning
While convolutional neural networks (CNNs) have achieved remarkable performance on various supervised and unsupervised learning tasks, they typically consist of a massive number of parameters. This results in significant memory...
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