Education
M.Tech Software Engineering
Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaCGPA: 9.01 (Current)
Higher Education in Computer Science
Holy Cross School, Salem, Tamil Nadu, IndiaGrade: 81%
Experience
Project Intern - Internship
TiHAN-IIT HyderabadSkills: Artificial Intelligence (AI) | Android Development | Networking | Dataset | Transfer Learning.
Artificial Intelligence Externship
Google developers & SmartBridgeSkills: Artificial Intelligence (AI) | Flask | System Deployment | TensorFlow | Pandas (Software)
Deep Learning Research Intern
Centre of Excellence for Autonomous Vehicles Research, ARC-VITSkills: Artificial Intelligence (AI) | Python (Programming Language)| TensorFlow | LiDAR | Socket Programming
Top Skills
Artificial Intelligence (AI)
Android Development
Python (Programming Language)
Cloud Computing
Data structures and Algorithm
NLP Applications
Java Application Development
Machine Learning
Problem solving
Website GUI Design & Deployment
Sensor Interfacing
Projects
Voice Assisted Quiz App for visually impaired students
View Project ImplementationWith its innovative mobile application, the Voice-Controlled Quiz App for Visually Impaired Students has the potential to revolutionize the educational experience for those with visual impairments. This ground-breaking program has been painstakingly designed to break through conventional barriers and herald in a new era of easily accessible and captivating learning experiences. Through the use of voice recognition and speech synthesis technology, the app aims to transform the way visually impaired students of all ages interact with educational quizzes, therefore empowering them.
FarmersAI
An Android App with Cloud Integration, Farmers can use this app to scan the leaf of their plant/crop and identify any disease if they are affected. The app works by sending the leaf image to the cloud where our AI models trained to detect disease make a prediction and send them back to the app, additionally, the app provides an interface for Agri scientists to evaluate the model results and correct them in real time.An Android App with Cloud Integration, Farmers can use this app to scan the leaf of their plant/crop and identify any disease if they are affected. The app works by sending the leaf image to the cloud where our AI models trained to detect disease make a prediction and send them back to the app, additionally, the app provides an interface for Agri scientists to evaluate the model results and correct them in real time.
WebApp for XSS Detection
View Project ImplementationAn XSS scanner that looks and scans for XSS patterns for a given URL, I have used six machine learning models that are trained on the XSS Dataset (Normal URL + XSS URL) for predicting whether the given URL is safe or unsafe. The results of all these six models are used to calculate the vote (Majority voting) score. Based on the score value and threshold (0.50% > XSS) the decision of whether the given URL is XSS or NON XSS is predicted. This model combined with GUI offers a functional website where users can scan a URL to determine whether it's safe or unsafe.An XSS scanner that looks and scans for XSS patterns for a given URL, I have used six machine learning models that are trained on the XSS Dataset (Normal URL + XSS URL) for predicting whether the given URL is safe or unsafe. The results of all these six models are used to calculate the vote (Majority voting) score. Based on the score value and threshold (0.50% > XSS) the decision of whether the given URL is XSS or NON XSS is predicted. This model combined with GUI offers a functional website where users can scan a URL to determine whether it's safe or unsafe.
Caption & Hastags Generator and image enhancement
View Project ImplementationA innovative web application combines advanced image analysis, caption generation, hashtag suggestions, and photo editing to give a full set of tools for image management and optimisation. Users can easily enhance their photographs and receive insightful information to improve their online presence by utilising advanced tools.
Bus Yatra
BUS YATRA, is a mobile application that will track the current bus location and enable the government and bus operators to keep records of the most frequent and high-demand routes and the total fare amount generated, It is simple to implement as no GPS need to be installed in bus rather we use the mobile of the driver to track the bus, the application will also make payments easier by making all the payments digitalBUS YATRA, is a mobile application that will track the current bus location and enable the government and bus operators to keep records of the most frequent and high-demand routes and the total fare amount generated, It is simple to implement as no GPS need to be installed in bus rather we use the mobile of the driver to track the bus, the application will also make payments easier by making all the payments digital.
UAV Controller
This app is a part of the Tihan IIT Hyderabad Rover Project, It is used to control the rover using an Android app wirelessly and also streams video of cameras in the rover in real-time using a 5G network.This app is a part of the Tihan IIT Hyderabad Rover Project, It is used to control the rover using an Android app wirelessly and also streams video of cameras in the rover in real-time using a 5G network.
Publications
LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems
Elsevier Expert Systems with ApplicationsOur research addresses a significant gap in the field of autonomous driving systems, particularly in unstructured and diverse environments like India. We found that existing models, trained on datasets from structured environments, often fail to generalize in such challenging scenarios. To tackle this, we created and annotated a unique dataset, collected from various locations in Tamil Nadu, India, including both rural and urban areas with a mix of single and double-lane roads. The dataset, comprising 2464 instances of lane detection and obstacle detection, was manually annotated by our team. Apart from this, we have also used other open-source datasets in our research which have been mentioned in the paper.
View Publication
Comprehensive Analysis of Rice Leaf Disease Detection and Classification Models
SpringerMore than 60% of people in India consume rice in their day-to-day life [1] hence it is essential to identify the diseases at an early stage to prevent them from causing further damage which increases the yield of rice. The automatic way of detecting and diagnosing rice diseases is highly required in the agricultural field. There are various models proposed by researchers which detect paddy disease. We have classified and listed models based on their architecture such as CNN (Convolutional Neural Network), ANN (Artificial Neural Network), and ML (Machine Learning)
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Evolution of Artificial intelligence in field of health care
BODHI International Journal of Research in Humanities, Arts and ScienceArtificial intelligence is more accurate in work and fast in resolving problems and provides sharpen solutions, in health care industries Artificial intelligence improves clinical abilities and by using its data it could predict diseases and provide advanced treatments, as they are good at analyzing data they could specify the regions where a patient need improvement and suggest required diagnosis and treatments.
View PublicationEvents Organized
Hackathon Co-ordinator
Agrithon 2023Organized a 2-day hackathon called Agrithon. This hackathon was about developing AI solutions for Agriculture purpose, powered by TiHAN and NVIDIA.
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Workshop - Student Organizer
Industrial Applications of Unmanned Ground RoversOrganized a 5-day Skill development Workshop on Industrial Applications of Unmanned Ground Rovers, This workshop was Organized by VIT-SCORE School and Tihan IIT Hyderabad.
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