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algorithm preference » algorithm convergence (Expand Search)
preference formation » reference formulation (Expand Search), reference population (Expand Search), reference condition (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm preference » algorithm convergence (Expand Search)
preference formation » reference formulation (Expand Search), reference population (Expand Search), reference condition (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
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Contrast enhancement of digital images using dragonfly algorithm
Published 2024“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”
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S1 File -
Published 2024“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”
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S1 Dataset -
Published 2024“…In this study, we developed a computerized algorithm using the python package (pdfplumber) and validated against clinicians’ interpretation. …”
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PyNoetic’s online mode in action. Data is streamed from an Emotiv EPOC headset.
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Illustration of PyNoetic’s 2D and 3D simulation module with visual feedback.
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PyNoetic’s stimuli generation and recording module, which supports both ERP and SSVEP.
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PyNoetic’s pre-processing module, which supports filtering and artifact removal, including ICA.
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Illustration of recording paradigm with PyNoetic’s Stimuli generation and recording module.
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