Hasib Zunair

I am a researcher at The Tech Academy, where I work on embedded input devices, human computer interaction and computer vision. Alongside TTA, I am working on Deep Learning in Computer Vision supervised by Dr. Nabeel Mohammed.

I did my bachelors in Electrical and Electronic Engineering at North South University. My final year senior capstone involved an automated entry logging system using modern techniques, one of which involved real time facial recognition, where I was advised by Dr. Mohammad Monirujjaman Khan. During my undergraduate study, I squezzed in an internship at The Tech Lab, where I worked with embedded programming. I was also involved with IEEE, where I served as the founding chair of IEEE Robotics and Automation Society Student Branch Chapter advised by Dr. Lamia Iftekhar. I have also spent time at IUB, IEEE.

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My research interest lies in robotics with a focus in computer vision. The key aspects involve image & video processing with a pinch of deep learning. I have also worked on internet of things, embedded systems(motors and actuation) here. Below portrayed are my researh works and projects; I've done and have been involved so far. Representative papers are highlighted.

Unconventional Wisdom: A New Transfer Learning Approach Applied to Bengali Numeral Classification

Authors : Hasib Zunair, Nabeel Mohammad, Sifat Momen

An accuracy of 97.09% on the NumtaDB Bengali handwritten digit datasets test set, which was obtained by freezing intermediate layers.

The unconventional approach used in this paper produces better results than conventional transfer learning while taking less epochs and having almost half the number of trainable parameters. Resulting in a more optimized model.

Authors: Hasib Zunair

To detect vehicles in bangladesh (i.e rickshaws, vans etc.) and extract the current road condition in the form on intensity. YOLO Object detection is to be used which will be trained on a custom dataset of the vehicles in the context of Bangladesh. It will also have three classes - low, medium, high traffic.

Design and Implementation of an Automated Web Based Multifunctional Attendance System

(Best Paper Honorable Mention)

Implementation of an automated multifunctional attendance system which uses RFID, FINGERPRINT, and real time facial recognition. Entry logging is displayed on a website.

Provides security and smooth data aquisition.

Authors: Hasib Zunair

(6th place overall)

A deep learning CNN architecture named VGG16 is used as a baseline to recognize bengali handwritten digits. Testing accuracy of 97.5% is achieved which led to the 6th position overall among 50 teams in the kaggle competition.

Design and Implementation of an IOT based Monitoring System for Inland Vessels using Multiple Sensor Network

The paper includes designing and implementing a wireless sensor network with a real time web application for monitoring multiple ships to prevent catastrophic events due to overloading.

The idea consists of four main parts: Detection Module, GPS tracker, communication system (NRF24L01+) and software application for web interface.

Authors: Hasib Zunair

This project demonstrates a hand gesture recognition system using skin color segmentation and image filtering techniques.

Authors: Hasib Zunair

A program that detects when your boss is approaching and changes the computer screen instantly. It uses the classical cascade classification algorithm for facial recognition. Upon detecting the boss, the interface changes the computer screen. It is a fun way to implement facial recognition.

Design and Implementation of Security Patrol Robot using Andrioid Application

Here proposed, is a low-cost autonomous mobile security robot based on a multisensor system.The robot is mobile and provides fully autonomous patrolling in a defined area.

It also provides four kinds of alarming systems via which notification of security violation is sent.

Authors: Aiman Snigdha, Tanzil Sharia, Hasib Zunair

An unmanned land rover was built to monitor different parameters in the mangrove forest for research purposes. The parameters included different gases and climate changes from surroundings.

Authors: Hasib Zunair

Here demonstrated is a strawberry detector using color segmentation and image filtering techniques. Morphological transformation is done to get a more smooth mask which is followed by drawing a contour over the original input image which is shown at the output.

Authors: Hasib Zunair

A mouse controller is developed using two green trackers. The colour values are tracked and mapped accordingly to the mouse pointer. Click and drag features added just like in the mouse.

(1st Position)

Authors: Hasib Zunair, Aiman Snigdha, Tanzil Sharia

An unmanned underwater robot was build for marine research and patrol purposes. In the demo, a depth of 2 feet was achieved.

Authors: Hasib Zunair

In this project, a flann based knn matcher using sift feature extractor and brute force matching is demonstrated. From both the algorithms, the features are extracted and the result is compared Sift extractor seemed to perform well.

Authors: Aiman Snigdha, Hasib Zunair, Tanzil Sharia, Abir Mahmud, Irfanul Haque, Shoumik Shekhar, Shahriar Kabir Rafi, Sajid Amin

A small unmanned ground vehicle (UGV) was developed as per requirements of the competition, the robot had the functions of moving autonomously across a storage area, counting items of a specific geometry in the warehouse, recording their ID tags, and carrying instrument payloads.

The robot obtained its surrounding visuals using a LIDAR Lite V3 and a regular camera. A 3D grayscale image is plotted with which the readings of the distance at every interval of time is measured and sent to a UI made in processing.