https://github.com/araj29011998/lane-marking-detection
Designed a deep learning-based lane marking detection system using CNNs & Hough Transform, addressing low visibility and faded lane challenges for autonomous driving.
https://github.com/araj29011998/research-papers
Published research paper with publication certificate.
https://github.com/aramis-lab/ad-ml
Framework for the reproducible classification of Alzheimer's disease using machine learning
https://github.com/aramis-lab/leaspy
LEArning Spatiotemporal Patterns in Python
https://github.com/aramis-lab/now-2023
Repository for the 2023 NeuroScience Open Workshop
https://github.com/aramis-lab/miccai-educational-challenge-2020
AD Classification using Clinica
https://github.com/aramis-lab/clinicaio
Python library for input/output management of all Clinica projects.
https://github.com/aramis-lab/tuto-doc
Toy library for documentation tutorial (summer 2025)
https://github.com/aramis-lab/clinica-pydra-freesurfer
Pydra tasks for FreeSurfer designed for Clinica
https://github.com/aramis-lab/clinica-pydra-ants
Pydra tasks for ANTs designed for Clinica
https://github.com/aramis-lab/clinicadl_bis
Framework for the reproducible processing of neuroimaging data with deep learning methods
https://github.com/aramis-lab/clinica_pipeline_fmri_preprocessing
fMRI-Preprocessing pipeline used for [Guillon et al., 2019]
https://github.com/aramis-lab/ad-dl
Classification of Alzheimer's disease status with convolutional neural networks.