grseb9s Goto Github PK

repos: 4.0K gists: 0.0

Name: GRS

Type: Organization

Bio: Geosciences & Remote Sensing

Location: ECUT

GRS's Projects

physics_gnn

Graph neural network based models with applications in particle physics

pi4u

Pi4U - High Performance Framework for Bayesian Uncertainty Quantification and Optimization

piccante

The hottest High Dynamic Range (HDR) Library

pickmt

Matlab codes for moment tensor phase picking and inversion.

Pixelwise Correlation-Based Landscape Classification (PiCo). PiCo, an R script, automates and regionalizes the Climate Landscape Response (CLaRe) metrics developed by Wallace et al 2016. This script performs a pixel-wise regression analysis to produce rasters whose correlation values can be evaluated to target buffelgrass.

piecewisecrf

The code for my master thesis "Modelling the Co-Occurrence of Semantic Labels with Conditional Random Fields"

piotrimagevideo

Piotr's Image & Video Matlab Toolbox with additional comments

pisaa_bnldd

Parallel and interacting simulated annealing approximation (Bayesian network learning application)

pix2pix

Image-to-image translation with conditional adversarial nets

pix2pix-pytorch

PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".

pix2pix-tensorflow

Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/

pix2pix-tensorflow-1

TensorFlow implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".

pixel_level_land_classification

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.