sebastianhafner Goto Github PK
Type: User
Company: KTH Royal Institute of Technology
Bio: PhD student at Geoinformatics, KTH Interested in applying DL to Earth observation data for urban applications.
Location: Stockholm, Sweden
Type: User
Company: KTH Royal Institute of Technology
Bio: PhD student at Geoinformatics, KTH Interested in applying DL to Earth observation data for urban applications.
Location: Stockholm, Sweden
Urban change detection for Sentinel-2 MSI imagery using a Siamese Network
This repository contains code for experiments using the winning mode for xView2 "xView2: Assess Building Damage" challenge and a simple implementation of our strong baseline.
[IGARSS'22]: A Transformer-Based Siamese Network for Change Detection
ChangeOS: Building damage assessment via Deep Object-based Semantic Change Detection - (RSE 2021)
ConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
Deep learning-based population mapping from Earth observation data in Sub-Saharan Africa
Unsupervised domain adaptation for global urban extraction using Sentinel-1 SAR and Sentinel-2 MSI data
Dual Stream U-Net architecture for urban change detection using Sentinel-1 and Sentinel-2 data fusion.
Frame-To-Frame Consistent Semantic Segmentation
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks
Nonconvex Relaxation Methods for MAP Inference in Discrete Markov Random Fields
Population Growth Mapping in Kigali using bi-temporal Sentinel-2 data and a Siamese network trained with weak supervision at the census level
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