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data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
learning algorithm » learning algorithms (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
data processing » image processing (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
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The overview of process of link by machine learning with local- and global- similarity-based scores.
Published 2025Subjects: -
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Data and code resources.
Published 2025“…Decoding from functional magnetic resonance imaging data revealed that solutions from the SF&GPI algorithm were activated on test tasks in visual and prefrontal cortex. …”
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Data Sheet 1_Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China.docx
Published 2025“…</p>Methods<p>UAV-LiDAR point clouds of Populus alba, Populus simonii, Pinus sylvestris, and Pinus tabuliformis from 12 sample plots, 2,622 tree in total, were obtained in North China, training and testing sets were constructed through data pre-processing, individual tree segmentation, feature extraction, Non-uniform Grid and Farther Point Sampling (NGFPS), and then four tree species were classified efficiently by two machine learning algorithms and two deep learning algorithms.…”
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Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx
Published 2025“…Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Supplementary file 1_Optimizing quantum convolutional neural network architectures for arbitrary data dimension.pdf
Published 2025“…The number of input qubits determines the dimensions (i.e., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. …”
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