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Agnes Schneider's Projects

caa2018-dl-workshop icon caa2018-dl-workshop

The basics of deep learning for archaeological site detection on remote sensor data

cainterprtools icon cainterprtools

R package to help interpreting Correspondence Analysis’ results

canopylazr icon canopylazr

R package to estimate leaf area density (LAD) and leaf area index (LAI) from airborne LiDAR point clouds

caseriation icon caseriation

R Package for contingency tables seriation via Correspondence Analysis

geocompr icon geocompr

Forthcoming book on geographic data with R

grass-lidar-talks icon grass-lidar-talks

Slides for my talks about processing lidar and general point cloud data in GRASS GIS

hsdar icon hsdar

:exclamation: This is a read-only mirror of the CRAN R package repository. hsdar — Manage, Analyse and Simulate Hyperspectral Data. Homepage: http://vhrz669.hrz.uni-marburg.de:8070/lcrs/, http://teledetection.ipgp.jussieu.fr/prosail/

huskydown icon huskydown

An R Markdown template using the bookdown package for preparing a PhD thesis at the University of Washington

julia-flowers icon julia-flowers

An experiment in R to create flowers inspired in the Julia Set

lai icon lai

R package to calculate leaf area index (LAI) from vegetation images

magaar icon magaar

R Package - Analyse geomagnetic data from archaeological context

mask_uav icon mask_uav

This is a project to create software that can annotate, train, using deep learning, and segment imagery data from UAVs or other platforms. The project uses Labelme and PixelLib to annotate and train/segment respectively. The intent is to enable automated feature detection on imagery.

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