rongtongxueya

MultiscalePINNs

wildfire-detection

Using Vision Transformers for enhanced wildfire detection in satellite images

DeepSatData

Automatically create machine learning datasets from satellite images

cropyieldArticle

FSODM

Official Code for paper "Few-shot Object Detection on Remote Sensing Images"

SatelliteVu-AWS-Disaster-Response-Hackathon

Satellite Vu submission for the AWS Disaster Response hackathon

Awesome-Few-Shot-Class-Incremental-Learning

Awesome Few-Shot Class-Incremental Learning

vs-zsl

DeepForest-Wetland-Paper

Here are the codes for the "Deep Forest classifier for wetland mapping using the combination of Sentinel-1 and Sentinel-2 data" paper.

PhyDNet

Code for our CVPR 2020 paper "Disentangling Physical Dynamics from Unknown Factors for UnsupervisedVideo Prediction"

rongtongxueya

Config files for my GitHub profile.

CLIP-rsicd

ARSET-cropClassification

Crop Classification with Sentinel 1/2 - NASA ARSET Training: https://appliedsciences.nasa.gov/join-mission/training/english/arset-agricultural-crop-classification-synthetic-aperture-radar-and

ZeroGen

[EMNLP 2022] Code for our paper “ZeroGen: Efficient Zero-shot Learning via Dataset Generation”.

ECNN-on-SAR-data-and-Radiometry-data

Deep learning for Synthetic Aperture Radar(SAR) and Radiometry data. An Ensemble Convolutional Neural Network workflow is implemented with data acquisition, processing, labelling, creating model, training model and launching a model

crop-type-mapping

Source code to Rußwurm & Körner 2019. Self-Attention for Raw Optical Satellite Time Series Classification

SDGZSL

[ICCV2021] Official Pytorch implementation for SDGZSL (Semantics Disentangling for Generalized Zero-Shot Learning)

ZEST

Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization

wildfire_prediction

Wildfire prediction model for Springboard capstone

smoke_segmentation

Segmenting smoke plumes and predicting density from GOES imagery

ML_surrogate_model_wildfires

ML surrogate model which combines ROM, LSTM and DA for dynamical systems such as wildfires

tfvaegan

[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL

PredictingFireRisk

A #rspatial workshop on predicting fire risk in San Francisco

generalization-cellular-automata

Repository for the paper "Generalization over different cellular automata rules learned by a deep feed-forward neural network", https://arxiv.org/abs/2103.14886

DSD_paper_2020

The code for the paper titled "Crop Type Classification based on Machine Learning with Multitemporal Sentinel-1 Data", presented at the Digital System Design (DSD) 2020 conference.

Forest_wildfire_spreading_convLSTM

A personal trial to understand and simulate forest wildfire spreading from satellite data using Deep Learning (a model with a ConvLSTM layer).

CE-GZSL

Codes for the CVPR 2021 paper: Contrastive Embedding for Generalized Zero-Shot Learning

Zero-shot-knowledge-graph-relational-learning

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs

land-cover

Deep learning for land cover mapping

stconvs2s

Code for the paper "STConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for Weather Forecasting" (Neurocomputing, Elsevier)