Arushee Tomar's Projects
450- DSA Questions š„š„
Developed a drowsiness detection system utilizing real-time image analysis to monitor driver facial expressions, with a focus on eye movements.
Developed a drowsiness detection system utilizing real-time image analysis to monitor driver facial expressions, with a focus on eye movements.
Developed a sentimental model capable of analyzing customer input in text, audio, and image formats.The application extracts and preprocesses text, employs vectorization for input, and predicts emotional sentiment and ratings, presenting results on a user-friendly frontend
8th sem Final year Project of VTU
Genletter is an website where an user can generate any type of letter whether it can be an offer letter, internship letter,application letter etc. by filing the details in the input field. It is also flexible in the sense that all the input fields are not required while generating the pdf so that it can be done as per the needs.
The time and attendance Spot based on Geofencing
Virtually controlling computer using hand-gestures and voice commands. Using MediaPipe, OpenCV Python.
Social Media Abusive Speech Detector utilizing NLP methods and ML algorithms, including neural networks (multilayer perceptron), SVMs, NB classifiers, and logistic regression models to classify a given tweet or comment as sensitive
Perplexica is an AI-powered search engine. It is an Open source alternative to Perplexity AI
Real Time Sign Language Translator to Speech. This is the capstone project I worked on in my final year of BTech (Data Science) degree.
The application allows administrators to perform CRUD (Create, Read, Update, Delete) operations on student data.
It is a versatile tool for managing student records. It supports all CRUD operations, allowing users to search, view, edit, and delete student records from a database. The component provides a seamless user experience by handling data fetching, displaying search results in a tabular format, and offering intuitive controls for managing records.
The system will detect hand or pen tip gestures and on the bases of the gestures it recognizes, and paints accordingly on the screen.