arghadeep25 Goto Github PK

3d-keypoint-extraction

advanced-methods-in-image-processing

Digital Image Processing Assignments

arghadeep25.github.io

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

building-footprint-extraction-from-high-resolution-satellite-images

Building Segmentation from High Resolution 3-band Monocular Images

contour-extraction

data-science

data-structures-and-algorithms

C++ Data Structures

database

Geodatabase using Postgre SQL

docker-manual

face-detection

Face Detection using CNN, HoG and SSD

fourier-descriptor

Describing the shape of an object in an image based on its Fourier transform

google-test-example-cpp-project

Sample project to do Google Testing using CMake in VS Code

graphical-modelling-from-point-cloud-using-opengl

Implementation of OpenGL to build object and city model from 2D point cloud

grid-based-dbscan

kalman-filter

ml-algorithms

neural-network-activation-functions

numerical-optimization

The objective of this repository is to implement different linear and non-linear optimization algorithms. For e.g. Gradient Descent, Newton-Raphson, BFGS and Gauss-Newton

numpy

The fundamental package for scientific computing with Python.

photogrammetry-computer-vision

Implementation of different Photogrammetric algorithms to obtain Transformations, 2D and 3D homography, Camera Calibration

ros-bare-bones

The idea of this repository is to create a basic ROS framework in C++ on top of which any application can be build

ros-bare-bones-sub

ros-pub-sub-vscode

The Git repo offers a basic ROS example for publisher-subscriber communication, tailored for VS Code. It includes minimalistic code, ROS integration, and VS Code setup. Designed for simplicity, it's ideal for learning ROS and VS Code integration.

ros_multiple_devices

The idea of this repo is to demonstrate how to deploy a ROS system across multiple machines

statistics

Implementation of different statistical methods on linear and non-linear problems for obtaining functional model, stochastic model, standard deviation,