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awesome-deep-learning-resources

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

binary_image_classification_deep_learning

Here we classified cell if its malaria infected or not

canopy_height_model

This code uses data collected by the NEON Airborne Observation Platform to distinguish spectral properties of chronic N and P addition

cerrado

classifying-different-crop-categories-using-hyperspectral

Nowdays Hyperspectral data are more widely used for crop classificatio. We used a modified version of U-net for the purpose of Classification.

data-visualization-and-analysis

It has all the code used by the beginner during practice

datacube-core

Open Data Cube analyses continental scale Earth Observation data through time

dataflowr-notebooks

code for deep learning courses

datasciencecoursera

This repo contains the files related to the Coursera Data Science Specialization

deep-learning-for-multiclass-segmentation-of-satellite-images

INCOMPLETE

detectree2

Python package for automatic tree crown delineation based on the Detectron2 implementation of Mask R-CNN

dl-keras-tf

rstudio::conf(2020) deep learning workshop

envdatsci22

Code sprints and project folder for CEE/EAR 609

eo-learn-examples

Examples of Earth observation workflows that extract valuable information from satellite imagery, giving you hints and ideas how to use the EO data.

flood-detection-algorithm-using-gee

A JavaScript code developed in Google Earth Engine (GEE) Platform to Detect Flooded Area along with Affected Population

floodnet

Official implementation of https://arxiv.org/abs/2105.08655 paper

gee-tutorials

This code base is collection of codes that are freely available for google earth engine. This is the collection of tutorials prepared by multiple individuals that were shared publicly as documents for learning purposes. These documents has been converted to web pages and are made easy access to the normal users via web page.

gee_multitemporal_classification

geospatial

glacier_mapping

hands-on-time-series-analylsis-python

Source Code for 'Hands-on Time Series Analysis with Python' by B V Vishwas and Ashish Patel

landsat-classification-using-convolution-neural-network

Source code and files mentioned in the medium post titled "Is CNN equally shiny on mid-resolution satellite data?" available at https://towardsdatascience.com/is-cnn-equally-shiny-on-mid-resolution-satellite-data-9e24e68f0c08

landsat-sentinel-fusion

Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa

landslide-displacement-forecasting-using-seven-deep-learning-architectures-and-monitoring-data

lidar-and-hyperspectral-fusion-classification

Landcover classification using the fusion of HSI and LiDAR data.

llm-cookbook-for-open-science

Cookbook to use LLMs effectively for sciences, in various levels of expertise

open-geo-tutorial

Tutorial of basic remote sensing and GIS methodologies using open source software (GDAL in Python or R)

python_for_image_processing_apeer

https://www.youtube.com/playlist?list=PLHae9ggVvqPgyRQQOtENr6hK0m1UquGaG

python_for_microscopists

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1