Search alternatives:
largest decrease » marked decrease (Expand Search)
larger decrease » marked decrease (Expand Search)
learning leads » learning goals (Expand Search), learning methods (Expand Search)
leads decrease » mean decrease (Expand Search), levels decreased (Expand Search), deaths decreased (Expand Search)
largest decrease » marked decrease (Expand Search)
larger decrease » marked decrease (Expand Search)
learning leads » learning goals (Expand Search), learning methods (Expand Search)
leads decrease » mean decrease (Expand Search), levels decreased (Expand Search), deaths decreased (Expand Search)
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Model and learning rule.
Published 2025“…The right column has the same pre- and postsynaptic activities as the left column, only in reverse order. In <b>(C)</b>, the learning rule with parameters is used, while in <b>(D)</b> Only in the latter the synaptic weight changes are preserved (in reverse order), while in <b>(C)</b>, postsynaptic activity before presynaptic activity leads to a net weight decrease. …”
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Evaluation of the effectiveness of double task.
Published 2025“…Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. …”
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Evaluation of the effectiveness of pruning.
Published 2025“…Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. …”
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The summary of ablation experiment.
Published 2025“…Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. …”
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Schematic of SADBIFB.
Published 2025“…Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. …”
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Schematic of the residual attention block.
Published 2025“…Yet, these methods still encounter two primary challenges. Firstly, deep learning methods are sensitive to weak edges. Secondly, the high cost of annotating medical image data results in a lack of labeled data, leading to overfitting during model training. …”
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Image 2_Computed tomography and magnetic resonance imaging features of primary liver perivascular epithelioid cell tumor with renal angiomyolipoma: a case report and literature rev...
Published 2025“…The enhancement slightly decreased in the equilibrium phase and the delayed phase. …”