بدائل البحث:
process optimization » model optimization (توسيع البحث)
other optimization » after optimization (توسيع البحث), step optimization (توسيع البحث), convex optimization (توسيع البحث)
image process » damage process (توسيع البحث), image processing (توسيع البحث), simple process (توسيع البحث)
primary data » primary care (توسيع البحث)
data other » data over (توسيع البحث)
process optimization » model optimization (توسيع البحث)
other optimization » after optimization (توسيع البحث), step optimization (توسيع البحث), convex optimization (توسيع البحث)
image process » damage process (توسيع البحث), image processing (توسيع البحث), simple process (توسيع البحث)
primary data » primary care (توسيع البحث)
data other » data over (توسيع البحث)
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Features selected by optimization algorithms.
منشور في 2024"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …"
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Image processing workflow.
منشور في 2020"…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …"
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A* Path-Finding Algorithm to Determine Cell Connections
منشور في 2025"…</p><p dir="ltr">Astrocytes were dissociated from E18 mouse cortical tissue, and image data were processed using a Cellpose 2.0 model to mask nuclei. …"
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
منشور في 2025"…This strategy </p><p dir="ltr">not only improves detection efficiency and accuracy but also supports early diagnosis and treatment planning, </p><p dir="ltr">leading to better patient outcomes. By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …"
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Hybrid feature selection algorithm of CSCO-ROA.
منشور في 2024"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"
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FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology
منشور في 2024"…Here, we show that ML algorithms trained with an FEP-augmented data set could achieve comparable predictive accuracy to data sets trained on experimental data from biological assays. …"