Kesshi Jordan's repositories
Cluster-viz
Browser-based visualization tool for cluster-based quality-control of tractography output to facilitate modeling of white matter fascicles
dipy_workshop
Materials for teaching the Dipy workshop for the 2018 OHBM Hackathon.
Kesh_Autoseg_Tools
This is a set of tools associated with automatically segmenting tractography datasets using a combination of two complementary approaches: streamlines included in a fascicle model are identified based on 1) anatomical connectivity priors based on Freesurfer-derived regions of interest (ROIs) in the subject’s native space and 2) shape priors based on 3D streamline bundle atlases applied using Recobundles. The code for a methodology generating bundle atlases is also included, as well as useful command-line helper scripts such as identification of outliers, filtering, and merging functions.
AFQ
Automated Fiber Quantification
brainbrowser-minimal-example
Minimal BrainBrowser example, BrainBrowser -- https://brainbrowser.cbrain.mcgill.ca
kesshi_sandbox
Sandbox repo for trying things
medulina.github.io
Brain segmentation game
nibabel
Python package to access a cacophony of neuro-imaging file formats
nipype
Workflows and interfaces for neuroimaging packages
Publication_Repository
sharing methods and interesting science
scikit-learn
scikit-learn: machine learning in Python
shared_scripts
sharing miscellaneous scripts
Synthetic-video-generation-for-Autonomous-cars
A huge challenge for autonomous vehicles(ACs) is to have a dataset that captures real-world multitudinous driving conditions. The currently available video datasets are not annotated & most of them aren't high resolution videos which is again an impediment for object detection. I am excited to solve this problem by annotating & generating photo-realistic synthetic video dataset for ACs using DeepLab, conditional GANs.
touchscreen_ml
for our machine learning class