بدائل البحث:
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
each algorithm » search algorithm (توسيع البحث), means algorithm (توسيع البحث)
trained using » obtained using (توسيع البحث), examined using (توسيع البحث), determined using (توسيع البحث)
element each » element data (توسيع البحث), element mesh (توسيع البحث)
using algorithm » using algorithms (توسيع البحث), routing algorithm (توسيع البحث), fusion algorithm (توسيع البحث)
each algorithm » search algorithm (توسيع البحث), means algorithm (توسيع البحث)
trained using » obtained using (توسيع البحث), examined using (توسيع البحث), determined using (توسيع البحث)
element each » element data (توسيع البحث), element mesh (توسيع البحث)
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The mAP for all algorithms and 80% of the data used for training.
منشور في 2024"…<p>The mAP for all algorithms and 80% of the data used for training.</p>…"
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The mAP for all algorithms and 50% of the data used for training.
منشور في 2024"…<p>The mAP for all algorithms and 50% of the data used for training.</p>…"
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The mAP for all algorithms and 60% of the data used for training.
منشور في 2024"…<p>The mAP for all algorithms and 60% of the data used for training.</p>…"
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Training algorithm flow.
منشور في 2024"…<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. …"
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List of the time used by each algorithm.
منشور في 2024"…In this manner high quality and common samples are randomly selected for training the classifier. Finally, to solve the issue of concept drift, EDAC designs and implements an ensemble classifier that uses a self-feedback strategy to determine the initial weight of the classifier by adjusting the weight of the sub-classifier according to the performance on the arrived data chunks. …"
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Characteristics of training algorithms.
منشور في 2025"…The issue of overfitting is significantly resolved, unlike in the case of the Backpropagation Neural Network (BPNN), which is used as a benchmark for comparison. Overall, the proposed algorithm significantly improves data training accuracy and generalization performance.…"
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Performance metrics (compared with DXA-based measurement) for different prediction algorithms using all predictors in training data.
منشور في 2025"…<p>Performance metrics (compared with DXA-based measurement) for different prediction algorithms using all predictors in training data.</p>…"
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The run time for each algorithm in seconds.
منشور في 2025"…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …"
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