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DeepInsight: A methodology to transform a non-image data to an image for convolution neural network architecture
Nature
DeepInsight enables feature extraction through the application of CNN for non-image samples to seize imperative information and shown promising results.
63 months ago
Restricted Boltzmann Machines for Feature Extraction, Explained
Towards Data Science
Restricted Boltzmann Machine (RBM for short) is a versatile feature extraction method. It boasts solid theoretical foundations,...
36 months ago
Fractal Dimension Image Processing for Feature Extraction and Morphological Analysis: Gd
Wiley Online Library
This is the first study to look at segmented SEM images for fractal dimension (FD) and other statistical criteria, including average, maximum, minimum,...
18 months ago
Foundation model for cancer imaging biomarkers
Nature
Foundation models in deep learning are characterized by a single large-scale model trained on vast amounts of data serving as the foundation...
7 months ago
Efficient cross-validation traversals in feature subset selection
Nature
Sparse and robust classification models have the potential for revealing common predictive patterns that not only allow for categorizing...
22 months ago
Morphological profiling by high-throughput single-cell biophysical fractometry
Nature
Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles a smaller part of...
18 months ago