Name: Constantin Pape
Type: User
Company: University Goettingen
Bio: Group leader at Uni Goettingen.
I work on deep learning and computer vision solutions for large-scale bio-image analysis.
Twitter: cppape
Location: Goettingen, Germany
Blog: https://user.informatik.uni-goettingen.de/~pape41/
Constantin Pape's Projects
JSON for Modern C++
TEASAR derived skeletonization of 3D densely labeled images.
Open Source Differentiable Computer Vision Library for PyTorch
lazy parallel ondemand zero copy numpy array data flows with caching and dirty propagation
Solving LPs with convergent message passing
Repo for machine learning project.
MALIS structured loss function for supervised learning of segmentation and clustering
Super-Fast mAP evaluation for large 3D volumes, Visual Computing Group at Harvard University
Fast Runtime-Flexible Multi-dimensional Arrays and Views for C++
Benchmarking c++ multiarrays
Multicut workflow for processing large-scale connectomics data, using luigi for pipelining.
Lightweight torch wrapper for bio-medical segmentation
A conda-smithy repository for mobie_utils.
Ilastik mutex watershed prototype
The mutex watershed for image segmentation
Not HDF5
napari: a Qt- and VisPy-based ndarray visualization tool
A reader for zarr backed OME-NGFF images
Bundling different metrics for evaluation of Neurosegmentation
Neural network babysteps with tensorflow
Next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.
nifty cPP and Python
A conda-smithy repository for nifty.
Wrapping the nifty rag to ilastik
Experimental implementation of next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.
A C++ Library for Discrete Graphical Models