Pinned Repositories
apriltag
AprilTag is a visual fiducial system popular for robotics research.
cansat_aether_pdr
AIAA CanSat 2023 Project Design Report
CanSat_Materials
Telemetry, GCS and Electronics technical materials developed for CanSat 2023
COE-Asset-Identification
Complex and Non-linear dynamic Systems (CoE CnDS), Research Internship Materials
crack_detector
A deep neural network based pipeline for highlighting cracks in an image of concrete
ISSRDC-23
Repository of materials selected for poster presentation at the International Space Station R & D Conference, 2023
SIH-2023-Repo
A short repository containing materials developed for a single initial problem statement for Smart India Hackathon, 2023.
SIH-2023_Hardware-Finals
A repository of materials developed for the Hardware Edition finals of Smart India Hackathon, 2023.
tardis
TARDIS - Temperature And Radiative Diffusion In Supernovae
Uni-of-Washington_ML
Materials for a six week course on machine learning fundamentals and applications.
ojas200's Repositories
ojas200/COE-Asset-Identification
Complex and Non-linear dynamic Systems (CoE CnDS), Research Internship Materials
ojas200/apriltag
AprilTag is a visual fiducial system popular for robotics research.
ojas200/cansat_aether_pdr
AIAA CanSat 2023 Project Design Report
ojas200/CanSat_Materials
Telemetry, GCS and Electronics technical materials developed for CanSat 2023
ojas200/crack_detector
A deep neural network based pipeline for highlighting cracks in an image of concrete
ojas200/ISSRDC-23
Repository of materials selected for poster presentation at the International Space Station R & D Conference, 2023
ojas200/SIH-2023-Repo
A short repository containing materials developed for a single initial problem statement for Smart India Hackathon, 2023.
ojas200/SIH-2023_Hardware-Finals
A repository of materials developed for the Hardware Edition finals of Smart India Hackathon, 2023.
ojas200/tardis
TARDIS - Temperature And Radiative Diffusion In Supernovae
ojas200/Uni-of-Washington_ML
Materials for a six week course on machine learning fundamentals and applications.