Search alternatives:
initialization algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
process optimization » model optimization (Expand Search)
node initialization » random initialization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data node » data code (Expand Search), data model (Expand Search), data noise (Expand Search)
lens » less (Expand Search)
initialization algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), identification algorithm (Expand Search)
process optimization » model optimization (Expand Search)
node initialization » random initialization (Expand Search)
based process » based processes (Expand Search), based probes (Expand Search), based proteins (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data node » data code (Expand Search), data model (Expand Search), data noise (Expand Search)
lens » less (Expand Search)
-
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. …”
-
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. …”
-
3
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. …”
-
4
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. …”
-
5
-
6
-
7
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. …”
-
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. …”
-
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. …”
-
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. …”
-
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. …”
-
12
GSE96058 information.
Published 2024“…</p><p>Methods</p><p>Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. …”
-
13
The performance of classifiers.
Published 2024“…</p><p>Methods</p><p>Various artificial intelligence methods and techniques were employed in this study to achieve accurate outcomes. Initially, the data was organized and underwent hold-out cross-validation, data cleaning, and normalization. …”
-
14
Generalized Tensor Decomposition With Features on Multiple Modes
Published 2021“…Our proposal handles a broad range of data types, including continuous, count, and binary observations. …”
-
15
<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.…”