Search alternatives:
process optimization » model optimization (Expand Search)
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
seed process » creep process (Expand Search), seed proteins (Expand Search), based process (Expand Search)
based method » based methods (Expand Search)
lens » less (Expand Search)
process optimization » model optimization (Expand Search)
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
seed process » creep process (Expand Search), seed proteins (Expand Search), based process (Expand Search)
based method » based methods (Expand Search)
lens » less (Expand Search)
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Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging
Published 2022“…Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. …”
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2
Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging
Published 2022“…Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. …”
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3
Example of simulated calcium imaging dataset.
Published 2024“…The parameters for each operation such as the kernel size, sigma and footprint size were optimized. We then validated the utility of the algorithm with simulated data and freely moving nociception experiments using the lensless devices. …”
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4
Probability density of each bin of accuracy.
Published 2024“…The parameters for each operation such as the kernel size, sigma and footprint size were optimized. We then validated the utility of the algorithm with simulated data and freely moving nociception experiments using the lensless devices. …”
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5
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Seed mix selection model
Published 2022“…</p> <p> </p> <p>We applied the seed mix selection model using a binary genetic algorithm to select seed mixes (R package ‘GA’; Scrucca 2013; Scrucca 2017). …”
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7
Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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8
Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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9
Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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10
Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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11
DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf
Published 2022“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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12
adjoint-elastic-registration.zip from Organ registration from partial surface data in augmented surgery from an optimal control perspective
Published 2023“…After a discussion about the existence of solutions, we analyse the necessary optimality conditions and use them to derive a suitable optimization algorithm. …”
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13
SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…The central questions are: How do we optimally learn from data through the lens of models? …”
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14
SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…The central questions are: How do we optimally learn from data through the lens of models? …”
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15
<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
Published 2025“…We measured multiple stress markers over a year, including betalain content using our optimized method, where the species is spreading. Additionally, 3,735 digital images at the leaf level were taken. …”
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Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty
Published 2021“…The central questions are: How do we optimally learn from data through the lens of models? …”
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17
Massive Mixed Models in Julia
Published 2025“…In contrast, an approach based on penalized least squares can take advantage of sparse matrix methods to scale to models with millions of observations and handles nesting and crossing of random effects in a general way. …”