jaypige

jaypige's Stars

• HarisIqbal88/PlotNeuralNet

  Latex code for making neural networks diagrams

  Language:TeX21.8k2.8k

• RolnickLab/constrained-downscaling

  A project on how to incorporate physics constraints into deep learning architectures for downscaling or other super--resolution tasks.

  Language:Python674

• camlab-ethz/AI_Science_Engineering

  This repository is the official project page of the course AI in the Sciences and Engineering, ETH Zurich.

  Language:Jupyter Notebook8518

• ChristianSteger/HORAYZON

  Package to efficiently compute terrain parameters (like horizon, sky view factor, topographic openness, slope angle/aspect) from high-resolution digital elevation model (DEM) data. The package also allows to compute shadow maps and correction factors for downwelling direct shortwave radiation for specific sun positions.

  Language:Cython427

• thu-ml/DPOT

  Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"

  Language:Python291

• neuraloperator/Geo-FNO

  Geometry-Aware Fourier Neural Operator (Geo-FNO)

  Language:Jupyter Notebook16845

• minitorch/minitorch

  The full minitorch student suite.

  Language:Python1.8k353

• tum-pbs/pbdl-book

  Welcome to the Physics-based Deep Learning Book (v0.2)

  Language:Jupyter Notebook974154

• langnico/global-canopy-height-model

  This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.

  Language:Python13028

• ted-piotrowski/mapbox-gl-shadow-simulator

  Simulate terrain and structure shadows in a custom map layer

  465

• ESA-PhiLab/Major-TOM

  Expandable Datasets for Earth Observation

  Language:Jupyter Notebook13911

• Clay-foundation/model

  The Clay Foundation Model (in development)

  Language:Python34040

• microsoft/satclip

  PyTorch implementation of SatCLIP

  Language:Python22020

• BlakeRMills/MetBrewer

  Color palette package in R inspired by works at the Metropolitan Museum of Art in New York

  Language:R1.1k78

• amazon-science/earth-forecasting-transformer

  Official implementation of Earthformer

  Language:Jupyter Notebook35861

• vitusbenson/greenearthnet

  Code for Benson et. al., CVPR (2024) - Multi-modal learning for geospatial vegetation forecasting

  Language:Python323

• facebookresearch/HighResCanopyHeight

  This repository provides inference code to compute canopy height maps from aerial images, as described in the paper "Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar".

  Language:Python19837

• Jack-bo1220/Awesome-Remote-Sensing-Foundation-Models

  82381

• isaaccorley/pytorch-enhance

  Open-source Library of Image Super-Resolution Models, Datasets, and Metrics for Benchmarking or Pretrained Use

  Language:Python7610

• Evoland-Land-Monitoring-Evolution/sentinel2_superresolution

  Super-resolution of 10 Sentinel-2 bands to 5-meter resolution, starting from L1C or L2A (Theia format) products.

  Language:Python547

• wri/sentinel-tree-cover

  Image segmentations of trees outside forest

  Language:Jupyter Notebook16038

• jonathanventura/canopy

  Automatic tree species classification from remote sensing data

  Language:Python3710

• remis/mining-discovery-with-deep-learning

  Mining and tailings dam detection in satellite imagery using deep learning

  Language:Jupyter Notebook249

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  8.4k1.4k

• worldstrat/worldstrat

  The WorldStrat Dataset

  Language:Jupyter Notebook23525

• erichson/SuperBench

  Language:Jupyter Notebook358

• allenai/satlaspretrain_models

  Language:Jupyter Notebook7012

• microsoft/torchgeo

  TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

  Language:Python2.6k322

• DigiRL-agent/digirl

  Official repo for paper DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning.

  Language:Python20016

• cneben/react-maplibre-standalone

  :mountain_snow: Sample React MapLibre visualization with standalone GIS datas

  Language:TypeScript184