1. Face Recognition based Employee Attendance system

Attendance is of prime importance for both the teacher and student of an educational organization. So, it is very important to keep a record of attendance. The problem arises when we think about the traditional process of taking attendance in the classroom. Calling the name or roll number of the student for attendance is not only a problem of time- consuming but also needs energy. So an automatic attendance system can solve all the above problems.

This project introduces an involuntary attendance marking system, devoid of any kind of interference with the normal teaching procedure. The system can be also implemented during exam sessions or in other teaching activities where attendance is highly essential. This system eliminates classical student identification such as calling the name of the student or checking the respective identification cards of the student, which can not only interfere with the ongoing teaching process but also can be stressful for students during examination sessions.

All scenarios are with respect to students and faculty but this issue also occurs in companies where students are replaced with employees and faculty are replaced by the manager.

Mentor: Mrugendrasinh Rahevar

Student: Jay Desai (17CE025)

Technology: Django Framework, OpenCV

Project Status: Completed

2. Digi Report: Machine Learning-based Pathology Report Analysis

2. Ph.D. Admission Portal

Create an online Admission portal for Ph.D. Admission for CHARUSAT University. Portal should provide the following functionalities.

1. Login and Registration

2. Role-based access

3. Dashboard for all Users.

4. Fill-up Admission Page

5. Generate pdf and email application to the applicant.

6. Auto approval of the application

7. Send confirmation and reject email to the applicant

Mentor: Mrugendrasinh Rahevar, Martin Parmar

Technology: NodeJS or PHP(Laravel Framework) or Python(Django/Flask Framework) or Java Spring Boot

Project Status: Closed

2. Skeleton Based Action recognition using Transformer

The Human body skeleton acted as a spatiotemporal graph, which is the key inspiration for researchers to implement a GCN-based method for action recognition. Most recently proposed GCN-based techniques combine convolutions with a self-attention mechanism to extract the most informative joint of a human skeleton and increase the model accuracy. The traditional multi-head attention method absorbed all attention heads equally, whereas in most situations, especially for extended skeleton sequences, not all attention heads are expected

Mentor: Mrugendrasinh Rahevar

Project Status: Complete

5. Self Driving Car

An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars combine a variety of techniques to perceive their surroundings, including radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage.

Task1: Detecting Lane Lines (basic)

Task2: Traffic Sign Classification

Task3: Vehicle Detection and Tracking

Dataset: https://github.com/SullyChen/driving-datasets

Mentor: Mrugendrasinh Rahevar

Project Status: closed