AdityaNG/Low-Cost-Hardware-Accelerated-Vision-Based-Depth-Perception-for-Real-Time-Applications

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Language
C++
License
GNU General Publi...
Created almost 4 years ago
Updated about 1 year ago

AdityaNG/Low-Cost-Hardware-Accelerated-Vision-Based-Depth-Perception-for-Real-Time-Applications

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CVMI 2022: A library to simplify disparity calculation and 3D depth map generation from a stereo pair

kan-gpt

The PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling

PAP_UE19CS306B

Python Application Programming

Jupyter Notebook

esp32-assembly

TCPServer

HP Assignement: PThreads. Build a multi-threaded server in C++, make use of PThreads for parallel programming.

TrajNet

ICRA 2024: A Comparative Study of RGB and Thermal Cameras for Night-Time Autonomous Navigation

PiCast

The very First version of the Android app for the Raspberry Pi Cast webapp

DriveLLaVA

Training LLaVA on the CommaVQ dataset to produce tokenized control signals for driving

Jupyter Notebook

socc_plotter

Semantic Occupancy 3D Plotter. This is the plotter made by the SOccDPT project to create fancy 3D visuals. You can use this for your own AV or Robotics visualization!

OpenMP_Notes

CS256_MPCA_Lab

Parallel-Prefix-Adder

Parallel Prefix Adders achieve logarithmic time complexity by means of parallelizing the operation. For an n bit prefix adder, the critical path is one xor gate, one and/or gate and log(n) modules.

general-navigation

General Navigation Models based on GNM, ViNT, NoMaD as a pytorch repo for quick and easy deployment

SOccDPT

AAIML 2024: 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints