Hyperspectral imaging (HSI) captures rich spectral data across hundreds of contiguous bands for diverse applications. Dimension reduction (DR) techniques are commonly used to map the first three ...
You’re living in a three-dimensional world. We all are. You can go left, right, forward, backward, up, and down. Now, picture a being that can pop in and out of your reality as if pressing a button, ...
This study aims to improve survival modeling in head and neck cancer (HNC) by integrating patient-reported outcomes (PROs) using dimensionality reduction techniques. PROs capture symptom severity ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...
Magnetic resonance imaging (MRI) is among the most commonly used imaging methods in preclinical studies as it non-invasively produces multiparametric data of tissues and organs. An animal organism’s ...
Here, we present Randomized Spatial PCA (RASP), a novel spatially aware dimensionality reduction method for spatial transcriptomics (ST) data. RASP is designed to be orders-of-magnitude faster than ...
Abstract: Surface electromyographic signals (sEMG) usually have high-dimensional properties, and direct processing of these data consumes significant computational resources. Dimensionality reduction ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback