Nikita-Belyakov/CLOUD_SNOW_SEGMENTATION
Research work for cloud and snow segmentation problem using meteorological satellite Electro-L №2 multispectral data, also suitable for GOES-16,17 multispectral data. This project includes all needed functions and utils for preprocessing multispectral data to make your own dataset for cloud and (or) snow segmentation problem
No commits in the last 6 months.
Stars
6
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Feb 01, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Nikita-Belyakov/CLOUD_SNOW_SEGMENTATION"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
satellite-image-deep-learning/techniques
Techniques for deep learning with satellite & aerial imagery
developmentseed/label-maker
Data Preparation for Satellite Machine Learning
NRCan/geo-deep-learning
Deep learning applied to georeferenced datasets
DPIRD-DMA/OmniCloudMask
OmniCloudMask is a Python library for fast, accurate cloud and cloud shadow segmentation in...
satellite-image-deep-learning/software
Software for working with satellite & aerial imagery ML datasets