Search alternatives:
process optimization » model optimization (Expand Search)
task optimization » based optimization (Expand Search), phase optimization (Expand Search), path optimization (Expand Search)
image process » damage process (Expand Search), image processing (Expand Search), simple process (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based task » based case (Expand Search), based test (Expand Search)
process optimization » model optimization (Expand Search)
task optimization » based optimization (Expand Search), phase optimization (Expand Search), path optimization (Expand Search)
image process » damage process (Expand Search), image processing (Expand Search), simple process (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based task » based case (Expand Search), based test (Expand Search)
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Demonstration of algorithm convergence.
Published 2025“…To maintain dynamic market equilibrium, we develop two types of pricing algorithms, one based on stepped price adjustments for selected sellers, and another based on smoothed adjustments for all sellers. …”
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Image processing workflow.
Published 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
Published 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
Published 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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Tasks with varying sizes.
Published 2024“…This results in the successful execution of most of the tasks within their deadline. In addition, <i>EOTE</i> − <i>FSC</i> modifies the task sequencing with a deadline algorithm for the fog node to optimally execute the offloaded tasks in such a way that most of the high-priority tasks are entertained. …”
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Assigning different sizes of task.
Published 2024“…This results in the successful execution of most of the tasks within their deadline. In addition, <i>EOTE</i> − <i>FSC</i> modifies the task sequencing with a deadline algorithm for the fog node to optimally execute the offloaded tasks in such a way that most of the high-priority tasks are entertained. …”
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Standard deviation for a varying number of tasks.
Published 2024“…This results in the successful execution of most of the tasks within their deadline. In addition, <i>EOTE</i> − <i>FSC</i> modifies the task sequencing with a deadline algorithm for the fog node to optimally execute the offloaded tasks in such a way that most of the high-priority tasks are entertained. …”
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