Developed a comprehensive image processing pipeline using
Streamlit that handles object segmentation, extraction, identification,
and text extraction. The pipeline generates annotated images and
provides outputs in JSON and summary tables. The project features
an intuitive UI for seamless navigation, with optimized image display
and annotation.
This project introduces a fluid dynamics image processing framework, using Proper Orthogonal
Decomposition (POD) and noise simulation techniques to analyze video data, providing a robust
toolkit for understanding fluid flow behavior.
The project developed a dynamic website for analyzing material strength using Bending Moment and
Shear Force diagrams. Utilizing HTML, CSS, JavaScript, and Chart.js, it showcased technical
proficiency, teamwork, and problem-solving skills.
A dynamic user interface was used along with an unusual method to develop an innovative
Minesweeper mine probability suggester that displays the probability of a mine as a percentage of
neighboring unopened cells and provides continuous feedback
Developed an image captioning system using VGG16 and LSTM deep
learning models, trained on the Flickr8K dataset. Implemented
preprocessing of images, tokenization of captions, demonstrating
expertise in computer vision and natural language processing.
A simple yet effective student list management system. This project allows for the storage and
management of basic student data, including name, email, roll number, and department. Key features
of the system include:
User authentication with login, logout, and registration functionality
Full CRUD (Create, Read, Update, Delete) operations for student data
Role-based permissions, ensuring that only admins can delete student information
This is a comprehensive e-commerce web application built with Django. The application provides a seamless shopping experience for users, featuring a dynamic product catalog, user authentication, cart functionality, secure checkout, and order tracking. The project aims to offer a scalable and secure platform for online shopping.
User Registration and Authentication
Dynamic Product Catalog
Shopping Cart and Checkout System
Order Management and Tracking
Admin Interface for Managing Products, Orders, and Users
Developed an image gender and age prediction web app using Flask.
Utilized a TensorFlow deep learning model for accurate predictions.
Implemented image upload, preprocessing, and dynamic result
display features.
The project uses a machine learning application to detect face mask wear using a convolutional
neural network, aiming to monitor and ensure compliance with mask-wearing guidelines during the
Covid-19 pandemic.
