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Jul 26, 2023 · We improve the original fractal dimension algorithm used to describe image texture roughness to suit a neural network. Moreover, in accordance ...
To address this problem, this article considers the consistency between similar data from the fractal perspective, introduces a priori knowledge, and proposes a ...
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The original fractal dimension algorithm used to describe image texture roughness to suit a neural network is improved, and prior knowledge of the quantized ...
We improve the original fractal dimension algorithm used to describe image texture roughness to suit a neural network. Moreover, in accordance with the improved ...
Jul 31, 2023 · It updates model weights through a parameter optimization strategy enabling more efficient learning when faced with new tasks with few samples.
Jul 12, 2023 · We survey promising applications and successes of meta-learning including few-shot learning, reinforcement learning and architecture search.
Apr 17, 2023 · Many computational problems and especially machine learning problems are related to the mathematical concept of fractal dimensionality. To ...
This learning strategy involves randomly selecting a number of few-shot classification tasks, using epoch training to acquire the meta-knowledge implicit in ...
May 11, 2024 · Third, exploring fractals' performance under few-shot learning should be investigated. Fractal pre-trained weights could reduce data needed for ...
Few-shot learning is a machine learning framework in which an AI model learns to make accurate predictions by training on a very small number of labeled ...
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