User: Guest  Login
Responsible:
Koch, Tobias 
Authors:
Rußwurm, Marc; Körner, Marco 
Author affiliation:
TUM: Chair of Remote Sensing Technology 
Publisher:
TUM: Chair of Remote Sensing Technology 
Title:
Temporal Vegetation Modelling using Long Short-Term Memory Networks for Crop Identification from Medium-Resolution Multi-Spectral Satellite Images 
Time of production:
01.06.2017 
Subject area:
BAU Bauingenieurwesen, Vermessungswesen 
Resource type:
Experimente und Beobachtungen / experiments and observations; Abbildungen von Objekten / image of objects 
Other resource types:
Training- and evaluation data; RNN networks 
Data type:
Bilder / images; mehrdimensionale Visualisierungen oder Modelle / models; Datenbanken / data bases 
Other data type:
Serialized data containing multispectral Sentinel 2 images and TensorFlow checkpoints 
Description:
Data supplements for the paper “Dataset for Temporal Vegetation Modelling using Long Short-Term Memory Networks for Crop Identification from Medium-Resolution Multi-Spectral Satellite Images” containing training- and evaluation data, evaluation methodology and neural network models. 
WWW:
This dataset is related to the publication https://mediatum.ub.tum.de/1369517 
Key words:
Remote Sensing, EarthVision2017, Temporal Modelling, Recurrent Neural Networks, Field Identification 
Technical remarks:
Follow github instructions ; https://www.github.com/TUM-LMF/fieldRNN ; https://www.lmf.bgu.tum.de/fieldRNN
View and download (5.4 GB total, 7 files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1370728):
rsync rsync://m1370728@dataserv.ub.tum.de/m1370728/ 
Language:
en 
Rights:
by, http://creativecommons.org/licenses/by/4.0