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Name: JM Mendoza
Type: User
Company: Rainforest Alliance
Bio: Senior GIS Officer
Location: Germany
Name: JM Mendoza
Type: User
Company: Rainforest Alliance
Bio: Senior GIS Officer
Location: Germany
Code samples for my book "Neural Networks and Deep Learning"
Tutorial of basic remote sensing and GIS methodologies using open source software (GDAL in Python or R)
M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.
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.
Processing of the 'Planet NICFI' Satellite Imagery
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
Python Deep Learning Cookbook, published by Packt
Build your neural network easy and fast
QGIS is a free, open source, cross platform (lin/win/mac) geographical information system (GIS)
Remote sensing image classification based on deep learning
Use Binder for reproducible satellite image analysis
Package to query the WDPA (protectedplanet.net) API
Resources for performing deep learning on satellite imagery
Deep Neural Network with keras-R (TensorFlow GUP backend): Satellite-Image Classification
Sample sample scripts and notebooks on processing satellite imagery
Automated download of Sentinel-2 L1C data from ESA (through wget) :http://olivierhagolle.github.io/Sentinel-download
Search and download Copernicus Sentinel satellite images
A multi-page streamlit app for geospatial
Tutorials of deep learning for computer vision.
Tensorflow tutorial from basic to hard
机器学习相关教程
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Some thing interesting about web. New door for the world.
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Some thing interesting about visualization, use data art
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Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.