Articles with "learning samples" as a keyword



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Learning from Few Samples with Memory Network

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Published in 2017 at "Cognitive Computation"

DOI: 10.1007/s12559-017-9507-z

Abstract: Neural networks (NN) have achieved great successes in pattern recognition and machine learning. However, the success of a NN usually relies on the provision of a sufficiently large number of data samples as training data.… read more here.

Keywords: memory network; neural networks; learning samples; limited data ... See more keywords

Learning with few samples in deep learning for image classification, a mini-review

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Published in 2023 at "Frontiers in Computational Neuroscience"

DOI: 10.3389/fncom.2022.1075294

Abstract: Deep learning has achieved enormous success in various computer tasks. The excellent performance depends heavily on adequate training datasets, however, it is difficult to obtain abundant samples in practical applications. Few-shot learning is proposed to… read more here.

Keywords: samples deep; classification; learning samples; deep learning ... See more keywords
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Optimal Learning Samples for Two-Constant Kubelka-Munk Theory to Match the Color of Pre-colored Fiber Blends

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Published in 2022 at "Frontiers in Neuroscience"

DOI: 10.3389/fnins.2022.945454

Abstract: Due to the dyeing process, learning samples used for color prediction of pre-colored fiber blends should be re-prepared once the batches of the fiber change. The preparation of the sample is time-consuming and leads to… read more here.

Keywords: kubelka munk; colored fiber; constant kubelka; learning samples ... See more keywords