simone codeluppi's Projects
3DMatch - a 3D ConvNet-based local geometric descriptor for aligning 3D meshes and point clouds.
Combination of Gamma Gaussian Mixture model and topological FDR for thresholding fMRI statistical maps.
A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations
ASHLAR: Alignment by Simultaneous Harmonization of Layer/Adjacency Registration
A curated list of awesome computer vision resources
A curated list of deep learning resources for computer vision
awesome-semantic-segmentation
generating A(n, d) codes in python
Bio-Formats is a Java library for reading and writing data in life sciences image file formats. It is developed by the Open Microscopy Environment (particularly UW-Madison LOCI and Glencoe Software). Bio-Formats is released under the GNU General Public License (GPL); commercial licenses are available from Glencoe Software.
CellProfiler is open-source cellular image analysis software.
Code snippets wrote for collaborators
Create minimal docker images from conda environments
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
HTCondor cluster manager for Dask.distributed (experimental)
My attempt at decoding the DNA of the Davos Bitcoin Challenge
A deep learning workshop, done from scratch, taught without any frameworks.
A python script to encode/decode arbitrary computer files into DNA sequences.
1st Edition of Elegant SciPy (O'Reilly Publishers)
Emacs notes and scripts
Fiji and ImageJ script
Spatial analysis of FISH data
A minimalist Pelican theme.
TensorFlow Deconvolution for Microscopy Data
Patched fonts for Powerline users.
Got Your Back (GYB) is a command line tool for backing up your Gmail messages to your local computer. It uses the standard IMAP protocol but also takes advantage of some custom Gmail IMAP extensions. For help with GYB, see the Getting Started Guide at https://github.com/jay0lee/got-your-back/wiki
GPU accelerated image/volume processing in Python
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Notebooks with image analysis notes. Thanks to everybody that provided inspiration and material
Import .mbox files into G Suite
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.