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Deep learning models for generation of precipitation maps based on NWP Data
Numpy arrays used in the paper "Deep learning models for generation of precipitation maps based on NWP". trn = training set vld = validation set tst = test set x =... -
Supplementary Material for "Process Data Properties Matter: Introducing Gated...
Supplementary material for the article: Heinrich, Kai ; Zschech, Patrick ; Janiesch, Christian ; Bonin, Markus: Process Data Properties Matter: Introducing Gated Convolutional... -
EHL Dataset EOSC Fast Track Grant Covid-19 Data Analysis with CXR Images (Cov...
The total size of the EHL Data is 305 MB, and the images’ resolutions vary quite a lot. Some Covid-19 images are about 1239x1024 and other normal images in the dataset are... -
Aerial images collected by an Unmanned Aerial Vehicle in Hermitage, Réunion -...
This dataset was collected by an Unmanned Aerial Vehicle in Hermitage, Réunion - 2023-12-01. Underwater or aerial images collected by scientists or citizens can have a wide... -
TPCOMP: Temporal Point Clouds of a wOrkpiece in the Machining Process
Temporal point clouds sampled from a workpiece in progress using 16 different machining tools. The datasets were created using a machining simulation in the Unit Industrial... -
Polymers Hyperspectral Imaging
Investigating State of the Art Hyperspectral Imaging Classification Models for Plastic Types Identification Polymers Dataset Description: The polymers dataset is a multiscene... -
Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals
Unsupervised semantic segmentation aims to automatically partition images into semantically meaningful regions by identifying global semantic categories within an image corpus... -
Generative Inpainting for Palimpsests: Background and Results
“Generative Inpainting for Palimpsests: Background and Results”, Manuscript Cultures in the Caucasus, Hamburg. The research for this presentation was funded by the... -
Semantic Self-adaptation: Enhancing Generalization with a Single Sample
The lack of out-of-domain generalization is a critical weakness of deep networks for semantic segmentation. Previous studies relied on the assumption of a static model, i. e.,...
