Projects

ColorSwapNet

The CycleGAN Wall Colorization Project leverages the power of CycleGAN and advanced image segmentation techniques to automatically change the color of walls in images. By accurately identifying wall regions through segmentation masks, the system enables realistic and seamless color transformations, making it an invaluable tool for interior design, virtual staging, and creative applications.

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Garbage Classification

This is a multimodal deep learning model using PyTorch to classify waste types by integrating image and text data which achieved an 85% test accuracy. Implemented a custom neural network combining a modified ResNet-50 architecture for image feature extraction and BERT for text processing. Optimized model performance through custom activation functions, fine-tuning techniques, and balanced class weighting, resulting in improved classification accuracy. Utilized tools like WandB for experiment tracking and performance visualization.

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News Pilot AI Agent

Engineered and launched an AI-powered web application to automatically summarize and present key insights from news articles, enhancing information accessibility and decision-making for users. Developed the backend using Python and the LangChain framework to construct an AI Agent that leverages News API and Tavily Search for dynamic web searching and data retrieval. Integrated OpenAI's language models to parse and analyze news content, encapsulating complex data processing tasks into a streamlined workflow. Designed a user-centric interface with Streamlit for ease of use and effective data presentation. Implemented Docker for application containerization and AWS Elastic Beanstalk for deployment.

Flight Reservation Web App

This project demonstrates a full stack application using React, Spring Boot and MySQL. It is a flight reservation system that lets users book seats on flights. Support is added for email notifications, flight crew functions like producing flight manifests, and admin functions for managing flights, aircraft, crew etc.

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