Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

“…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”

Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens by Hee-Jae Jeon (4614121)

“…Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. …”

Algorithms and evaluation metrics integrated in the COPS framework. by Teemu J. Rintala (19333003)

Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

Data Sheet 1_AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration.pdf by Ahmed Shamseldin (19759437)

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis by Qing Hu (152962)

Machine Learning-Driven Kinetic Elucidation for Sustainable Solvent-Free Continuous ε‑Caprolactone Production via Propionaldehyde-Mediated Nanocarbon Catalysis by Qing Hu (152962)

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

“…In this study, we report an ROI selection method using a series of adaptive binarizations with a gaussian method and morphological image processing. The parameters for each operation such as the kernel size, sigma and footprint size were optimized. …”

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

“…In this study, we report an ROI selection method using a series of adaptive binarizations with a gaussian method and morphological image processing. The parameters for each operation such as the kernel size, sigma and footprint size were optimized. …”

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

A data-driven machine learning approach for discovering potent LasR inhibitors by Christabel Ming Ming Koh (16798162)

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

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

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

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

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

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

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

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

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

“…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …”

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx by Liyin Zhang (6371999)

Data used to drive the Double Layer Carbon Model in the Qinling Mountains. by Huiwen Li (17705280)

“…The model divides the soil profile into topsoil (0-20 cm) and subsoil (20–100 cm) layers to match the SOC maps of the corresponding two layers generated by data-driven models. Each of these layers contains a young carbon pool (CY) with a higher decomposition rate and an old carbon pool (CO) with a lower decomposition rate. …”