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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.…
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Keywords:
memory network;
neural networks;
learning samples;
limited data ... See more keywords
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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…
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Keywords:
samples deep;
classification;
learning samples;
deep learning ... See more keywords
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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…
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Keywords:
kubelka munk;
colored fiber;
constant kubelka;
learning samples ... See more keywords