Purnendu Prabhat's Projects
As we all know that there is a lockdown of 21 days in India due to covid-19.So I thought that during this Quarantine period I should create some content to help beginners to start with computer vision.So this series is called as "21 days of Computer Vision". Would be uploading a video each day except sunday.This video series aims to help beginners. This is the YouTube channel named *The Caffeine Developers* please support us and Subscribe to our Channel as Everyday I will be Posting videos. https://lnkd.in/fKzEbqt
This repository contains study materials, links, codes, and tips for studying Artificial Intelligence and Deep Learning.
This repository has C programs that may be useful for students and people new to programming. This also contains programs that can be used as building blocks of more complex programs.
CloudSimSDN: a simulation framework for SDN-enabled cloud environments based on CloudSim
Simulating shitty network connections so you can build better systems.
This repository has some common codes that are always used by programmers. They can use it for their work as sometimes one needs to see some codes because they tend to forget things. The codes are well commented and easy to be used by even a novice.
Programs from the C Programming playlist on Mukul World YouTube Channel
A JavaScript visualization library for HTML and SVG.
The Web framework for perfectionists with deadlines.
These are programs for Data Structures course.
Omnet++ ring topology simulated network
Face detection using opencv and deep learning
The human-face is one of the easiest ways to distinguish the individual identity of each other. Face recognition is a very important task and has wide variety of application in security systems, authentication etc. Tracking the individuals can give us the valuable insights. In this project, we have developed Computer Vision based face recognition and tracking system with OpenCV and dlib. Our model is able to recognize and differentiate between known and unknown faces. For the tracing part, time when a person enters and leaves the premises is captured and the difference is calculated. The model was trained on dataset of 50 different individuals with 10 different images of each. We achieved state-of-the-art accuracy.
I will share my work with my faculty and classmates
A php wrapper for highcharts and highstock javascript libraries
File validation methods for the jQuery Validation plugin
Mininet for SDN cloud project
Open Source Computer Vision Library
C and C++ visualizer backend for Online Python Tutor
A collection of Osho discourses...