IEEE

Hyperspectral Unmixing for Additive Nonlinear Models With a 3-D-CNN Autoencoder Network

Abstract: Spectral unmixing is an important task in hyperspectral image processing for separating the mixed spectral data pertaining to various materials observed aiming at analyzing the material ...
GitHub

Generalized Additive Models in Python.

🚀 Version 0.12.0 out now! See release notes here. pyGAM is a package for building Generalized Additive Models in Python, with an emphasis on modularity and performance. The API is designed for users ...
ahajournals.org

Prediction of Cardiovascular Disease Events From the Photoplethysmograph Waveform

A photoplethysmographic pulse waveform (PPG) can be obtained optically by digital health technologies such as a smartphone or wearable devices. Features of the PPG may provide prognostic information ...
C&EN

An End-of-Life Plastic and Additive Flow Tracker Tool for Scenario Forecasting

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Plastics are widely used for their affordability and versatility in various ...
GitHub

Python Spatial Analysis Library

PySAL, the Python spatial analysis library, is an open source cross-platform library for geospatial data science with an emphasis on geospatial vector data written in Python. It supports the ...
The Lancet

Development and validation of an insulin resistance model for a population without diabetes mellitus and its clinical implication: a prospective cohort study

fResearch Center for Smart Sustainable Circular Economy, Tunghai University, Taichung, Taiwan gIntelligent Data Mining Laboratory, Department of Medical Research, Taichung Veterans General Hospital, ...
eLife

Putting perception into action with inverse optimal control for continuous psychophysics

Psychophysical methods are a cornerstone of psychology, cognitive science, and neuroscience where they have been used to quantify behavior and its neural correlates for a vast range of mental ...