ERGIN C CANKAYA's repositories
DroneLidarCode
Code (mostly R) to work with drone lidar data for forestry applications
ogh_summer_school_2020
Material for the session "Introduction to Deep Learning in R for the analysis of UAV-based remote sensing data"
python_for_image_processing_APEER
https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG
python_for_microscopists
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
allodb
An R package for biomass estimation at extratropical forest plots.
fastai
R interface to fast.ai
ForAINet
official source code for paper entitled "Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning"
GEDI-BDL
This repository provides the code used to create the results presented in "Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles".
GEDI4R
An R package for NASA’s GEDI Level 4A data download, processing and visualization.
lidRbook
The lidR package tutorials book :book:
NYCtrees
Here we produced an individual tree dataset including tree locations, height, crown area, crown volume, and biomass over the entire New York City, USA for 6,005,690 trees. Individual trees were detected and mapped from remotely sensed datasets along with their height and crown size information.
segment-anything-eo
Earth observation tools for Meta AI Segment Anything
segment-lidar
Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.
slidaRtools
Tools for lidar simulation and lidar processing
TreeCountSegHeight
Code for paper
TreeQSM
Quantitative Structure Models of Single Trees from Laser Scanner Data