Search alternatives:
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
pre optimization » art optimization (Expand Search), pso optimization (Expand Search), phase optimization (Expand Search)
while optimization » whale optimization (Expand Search), wolf optimization (Expand Search), phase optimization (Expand Search)
pre optimization » art optimization (Expand Search), pso optimization (Expand Search), phase optimization (Expand Search)
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Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX
Published 2021“…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …”
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…<pre>Figures at Thesis_RAMIS/Figs_PI related with PhD Thesis:<br><br>AN INFORMATION-THEORETIC SAMPLING STRATEGY FOR THE RECOVERY OF GEOLOGICAL IMAGES: MODELING, ANALYSIS, AND IMPLEMENTATION<br><br>Data for the <a href="https://github.com/fsantibanezleal/FASL_Thesis_RAMIS" rel="noreferrer" target="_blank">LaTeX </a>version of the document<br><br>In this thesis the role of preferential sampling has been systematically addressed for the task of geological facies recovery using multiple-point simulation (\emph{<i>MPS</i>}) and for the problem of short-term planning in mining. …”
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DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
Published 2024“…The ResNet-50 architectural model was used to implement deep transfer learning (DTL), undergoing -pre-training separately on the RadImageNet and ImageNet datasets. …”
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DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
Published 2021“…The molecular subtypes and AR expression in pre-treatment biopsy specimens were assessed. A total of 4,198 radiomics features were extracted from the pre-biopsy multi-parametric MRI (including dynamic contrast-enhancement T1-weighted images, fat-suppressed T2-weighted images, and apparent diffusion coefficient map) of each patient. …”
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