Algorithm for optimal decision determination in sequential decision-making. by Mariko I. Ito (5007323)

An example of a type of texture of binary preferred/non-preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging by Yingying Cao (4777638)

“…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. …”

Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging by Yingying Cao (4777638)

“…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. …”

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Example of simulated calcium imaging dataset. by Virgil Christian Garcia Castillo (19688355)

“…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. …”

Probability density of each bin of accuracy. by Virgil Christian Garcia Castillo (19688355)

“…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. …”

ROI masks generated when using 2.5 σ1. by Virgil Christian Garcia Castillo (19688355)

Testing algorithm for modified 2-tiered approaches to Lyme disease diagnosis. by Richard Porwancher (11413931)

Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”

Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”

Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”

Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”

DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf by Cédric Allier (4180903)

“…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”

An example of a type of a percent cover of preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

adjoint-elastic-registration.zip from Organ registration from partial surface data in augmented surgery from an optimal control perspective by Stéphane Cotin (3944129)

“…After a discussion about the existence of solutions, we analyse the necessary optimality conditions and use them to derive a suitable optimization algorithm. …”

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Omar Ghattas (4387300)

“…The central questions are: How do we optimally learn from data through the lens of models? …”

SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Umberto Villa (8400192)

“…The central questions are: How do we optimally learn from data through the lens of models? …”