Search alternatives:
surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
process optimization » model optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
lens » less (Expand Search)
surface optimization » surface contamination (Expand Search), resource optimization (Expand Search), swarm optimization (Expand Search)
process optimization » model optimization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
data surface » earth surface (Expand Search), metal surface (Expand Search), total surface (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
lens » less (Expand Search)
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1
Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens
Published 2021“…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. …”
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2
Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens
Published 2021“…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. …”
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3
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4
Example of simulated calcium imaging dataset.
Published 2024“…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. …”
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5
Probability density of each bin of accuracy.
Published 2024“…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. …”
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Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…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. …”
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8
Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…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. …”
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9
Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…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. …”
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10
Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF
Published 2022“…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. …”
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11
DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf
Published 2022“…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. …”
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12
PathOlOgics_RBCs Python Scripts.zip
Published 2023“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”
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13
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr">These provide mechanistic insights related to ion release potential, surface reactivity, and redox behavior.</p><p dir="ltr"><b>Data Cleaning and Normalization:</b></p><p dir="ltr">To ensure model reliability and generalizability, extensive preprocessing was undertaken:</p><p dir="ltr">Outlier management: Features with wide value ranges, such as hydrodynamic size or ROS scores, were log-transformed to reduce skewness.…”
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14
<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)
Published 2025“…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”