B.E.Pranav Kumaar (genpranav)

genpranav

Geek Repo

Location:Bangalore

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B.E.Pranav Kumaar's repositories

Yolov3-Object-Detection-from-Drone-feed

This project aims to implement real-time object detection from drone feed using YOLOv3 (You Only Look Once version 3) deep learning architecture. This project was implemented using tools and frameworks such as ROS, Gazebo, Ardupilot and MavROS

Four-Bar-Linkage-Based-Wiper-Mechanism

A through study of the design process of a 4 bar linkage mechanism and development of a pseudo control/dashboard application in matlab

4-bit-USR-using-HDL

Designing, Implementing and Simulating a 4-bit Universal Shift Register from scratch including all sub components in Hardware Description Language

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Brandes-Algorithm-Betweenness-Centrality

The goal of this project is to implement the Brandes algorithm for calculating betweenness centrality in a graph. The Brandes algorithm is a well-known algorithm for efficiently computing betweenness centrality in large, complex networks.

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Covid-Cough-Classification

Covid status classification using audio/voice file input

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Fundamentals-of-Google-Search-Engine

Detailed exploration of the Linear Algebra associated with the functional level changes achieved by the possible features of the Google Search Engine

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genpranav

Config files for my GitHub profile.

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L1-Norm-Problems-using-ADMM

Least Absolute Deviation(LAD), Huber Fitting and Least Absolute Shrinkage and Selection Operator(LASSO) solved using Alternating Direction Method of Multipliers(ADMM) approach, from a Linear Algebra standpoint along with the Machine Learning justification for exploration.

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Recursive-Backtracking-of-DFS-for-Mazes

The implementation of balanced and efficient maze generation and solving algorithms. Stochastic DFS based recursive backtracking to be specific.

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Regex-based-Pheonotype-Identifier

The Regex-based Casual Gene Identifier is a very simple and straight forward solution for gene identification using regular expressions, the goal is to parse excel files and predict the most probable gene segment corresponding to any phenotype.

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