Azure/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.

⭐ 282 | 🍴 96

isaaccorley/ChesapeakeRSC

Chesapeake RSC dataset introduced in "Seeing the roads through the trees: A benchmark for modeling spatial dependencies with aerial imagery"

⭐ 55 | 🍴 3

SEODEMON/EXTREME-PROXY-HARVESTER-AND-CHECKER

EXTREME PROXY HARVESTER AND CHECKER By Jeff Childers Harvest and Check Free Proxies. Check For Alive and Anonymous Proxies. This Requires NO Database and This Can Be Executed On A Shared Hosting Plan. PHP 5 or Higher.

⭐ 16 | 🍴 10

tetratech/baytrends

Evaluate long-term trends in the Chesapeake Bay using a Generalized Additive Modeling (GAM) approach

⭐ 12 | 🍴 4