Purpose: Evaluate the Facial Recognition when
streaming to localhost in three different evironments
(Jetson Nano, PC, Raspberry PI) by FPS and Latency
Build with: Python, Flask, Tensorflow, OpenCV and
Haarcascade algorithm
Recruitment System
Purpose: My goal is to develop a recruitment system
that ensures transparency in candidate profiles and enhances
facial image security. The proposed system will assist
recruiters in verifying the accuracy and transparency of
candidate profiles, thereby improving the reliability of the
recruitment process. Additionally, the system will protect
candidate facial images during facial recognition data
training, ensuring privacy is maintained.
Gift: As an author, I would like to offer you a
version of the above article and additional interesting
features as a token of appreciation for visiting my personal
page, in lieu of registering for a paid account on IEEE
Xplore to access the complete article.
Smart Shelf
Purpose: My main responsibility in this project is to
develop a Smart Shelf system utilizing RFID technology. This
involves utilizing C# and .NET framework to send and
retrieve data from devices, accessing APIs to gather book
information, inserting data into databases, sending signals
to other devices, and automatically calculating the location
of bookshelves. Additionally, I am responsible for
implementing the entire API of the RFID system to interact
with the database and GCP using Golang. Another
responsibility is deploying the entire system onto a mini PC
using Proxmox and configuring the network, services, and
automatic startup.
Build with: C#, Golang, Google Cloud Platform, MariaDB, Proxmox...