Tool for Quantitative Analysis and Visualization of Land Use and Land Cover Change.

Tubitak119e578 project: A novel detection and restoration pipeline for Phase Contrast Microscopy Time Series images

Learning the Intensity Analysis framework (Aldwaik & Pontius 2012) using the intensity.analysis R package implementation.

TUBITAK 119e578 project: A simple approach for Blank frame detection and video reconstruction

Materials for 2019 Tanintharyi land-cover regime shift paper (De Alban et al. 2019. Sustainability).

This is MATLAB script created and used via the Trinkaus-Randall Lab at Boston University for the analysis of epithelial cellular calcium signaling during wound healing.

Matlab class library to load, analyze, and extend Map Manager analysis.

Land use/cover change analysis in Mindoro Island, Philippines.

Satellite-based causal attribution of coastal water clarity degradation to nickel smelting expansion at Indonesia's Morowali Industrial Park using Bayesian structural time series, multi-algorithm changepoint detection, and Sentinel-2 land cover intensity analysis.

In this project, MRI images are compared and colored according to their intensity with GUI in Java.

Set of Jupyter notebooks and geospatial data developed by the MAPSPADES project to study desertification in the Algerian steppe using EO data.

Materials for 2020 Myanmar mangrove cover change analysis paper (De Alban et al. 2020. Environmental Research Letters).

Python Intensity Multi-Channel Profile Analyser (PyIMPA) is a scientific imaging tool written in Python that enables users to perform precise intensity profile analysis on both RGB and grayscale images.

This is a Python program used for averaging intensities summed over rows or columns in a specified region of interest for a collection of files of equal dimensions.

All about emotion recognition.