Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

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Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

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Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

Subjects:

Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

Subjects:

Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

Subjects:

Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

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Full-Field Dynamic Characterization of Super­hydrophobic Condensation on Biotemplated Nanostructured Surfaces by Emre Ölçeroğlu (1746853)

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Example psychometric functions for observer DHB. by Daniel H. Baker (11559693)

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Example images to illustrate denoising. by Daniel H. Baker (11559693)

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Maximum orientation bandwidth as a function of spatial frequency bandwidth (<i>ω</i>). by Daniel H. Baker (11559693)

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Illustration of an image denoising technique. by Daniel H. Baker (11559693)

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PSNR values for noisy (black line) and denoised (circles) images, calculated using Eq 8. by Daniel H. Baker (11559693)

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Thresholds for individual observers (a-c) and their average (d). by Daniel H. Baker (11559693)

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Example image, and statistics of image set. by Daniel H. Baker (11559693)

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Example log-Gabor filters of different orientation bandwidths for (a) polar-separable and (b) Cartesian-separable filters (see text for details). by Daniel H. Baker (11559693)

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Engineering Large-Area Antidust Surfaces by Harnessing Interparticle Forces by Samuel S. Lee (14658123)

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Supplemental Materials 2 by Ridhi Sahani (10514420)

“…<p><b>Supplemental Figure 2:</b> To validate the image processing algorithm and determine the appropriate subregion size, we first used our image processing algorithm with two manually-generated sets of test images of dark lines that approximated collagen fibers. …”

Alzheimer’s disease multiclass detection through deep learning models and post-processing heuristics by Rani Ghassan Al Rahbani (19349148)

“…This paper introduces a novel approach integrating two CNN algorithms, ResNet and EfficientNet, with a post-processing algorithm to enhance AD diagnosis. Empirical analyses on public datasets ADNI and OASIS evaluate the technique, leveraging the complementary strengths of the CNN models and a weighted averaging ensemble learning method. …”

Cerium Oxide Nanoparticle-Containing Colorimetric Contact Lenses for Noninvasively Monitoring Human Tear Glucose by Sijin Park (10808792)

“…These findings suggest that the CNP-PEG-GOx-laden contact lenses could be used along with a smartphone-based image-processing algorithm to noninvasively monitor human tear glucose.…”

PorosV3 by David Ocampo (9258749)

“…<p dir="ltr">Image-processing algorithm in MATLAB (2013a, The MathWorks, Inc., Natick, Massachusetts, USA) that automatically detects and quantifies pores in SEM images and measures their mean sectional area (i.e., size in μm²). …”