Olyna

Olyna's Stars

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  9.1k281241.5k

• aladdinpersson/Machine-Learning-Collection

  A resource for learning about Machine learning & Deep Learning

  Language:Python8k1191272.7k

• mdbartos/pysheds

  :earth_americas: Simple and fast watershed delineation in python.

  Language:Python76626200204

• kleok/FLOODPY

  Flood Python Toolbox

  Language:Jupyter Notebook17883533

• NRCan/geo-deep-learning

  Deep learning applied to georeferenced datasets

  Language:Python1631531152

• billpsomas/simpool

  This repo contains the official implementation of ICCV 2023 paper "Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?"

  Language:Python98212

• billpsomas/metrix

  This repo contains the official implementation of ICLR 2022 paper "It Takes Two to Tango: Mixup for Deep Metric Learning".

  Language:Python36824

• alekfal/pynasapower

  Download meteorological data from NASA POWER using a simple Python API client (https://power.larc.nasa.gov/).

  Language:Python20227

• alekfal/Auto-Sen2Cor

  This Software is created for the automatic atmospheric correction of Sentinel 2 Data using Sen2Cor algorithm given freely by E.S.A. For more details read 'README.md' given with this software.

  Language:Python10401

• alekfal/googlesat

  Download Sentinel 2 (L1C & L2A) from GCP without authentication.

  Language:Python7261

• alekfal/NDVI

  A simple python script for calculating NDVI index from earth observation data.

  Language:Python7302

• openEOPlatform/parcel-delineation

  Example of using openEO for parcel delineation based on deep learning.

  Language:Jupyter Notebook61100

• rslab-ntua/cropmaps

  Crop type mapping solution for MAGO Project (NTUA)

  Language:Jupyter Notebook4722

• alekfal/cropmaps

  Crop type mapping solution for MAGO Project (NTUA)

  Language:Jupyter Notebook3100