Projects

This project is part of Omdena San Jose, USA Chapter Challenge. It examines how healthcare, environmental conditions, lifestyle, socioeconomic status, and demographics impact life expectancy. It explores disparities between rural and urban areas and investigates the reasons for varying life expectancies across U.S. counties.

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The SmartScan Billing Assistant is a computer vision-based project designed to automate the process of calculating the total bill by detecting products and adding their prices using a camera, similar to a cashier. This project uses the YOLOv8 model for object detection and tracking. This is the MVP of the main project I did for a supermarket where I implemented the SmartScan billing system on more than 1200 products.

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This project demonstrates the use of YOLOv8 for detecting American Sign Language (ASL) gestures.

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This project showcases an object tracking system that employs YOLOv8 for detection and integrates a Kalman filter for tracking, thereby implementing the DeepSORT algorithm. It is designed to identify and follow objects within a video stream.

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Facial Emotion Recognition using YOLOv8: A real-time facial emotion detection system built with YOLOv8 and Flask. This project leverages a custom dataset with English-translated emotion labels and provides a user-friendly web interface for image uploads and live webcam analysis. Includes instructions for setup, usage, and training your own model.

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AI AdSense is a cutting-edge application designed to detect human presence, analyze their features, and generate personalized advertisements using advanced AI technologies.

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An interactive voice-based application using Local Language Models (LLMs) for querying product information. Developed with a React frontend and Flask backend, this project integrates with the Llama3 model but supports flexible model swapping. Originally for Garnier, it’s adaptable for any company's product inquiries.

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AI-Assistant-Builder is a flexible platform that enables users to create their own AI assistants tailored to any profession or field. By customizing some data and values, users can effortlessly build specialized AI assistants such as an AI Doctor or an AI Lawyer.

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This project leverages Generative Adversarial Networks (GANs) to enhance image resolution for various applications, using the Super-Resolution GAN (SRGAN) architecture. The project includes a Jupyter Notebook for model training and a detailed research paper documenting the methodology and results.

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This project uses a pre-trained CNN to identify dog breeds and distinguish between dog and non-dog images. This project, part of the Udacity AI Programming with Python Nanodegree, compares ResNet, AlexNet, and VGG models for accuracy and efficiency

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This project is part of the Coursera IBM Data Science Professional Certificate Capstone Project. The objective of this project is to explore neighborhoods in various cities and determine the best locations for establishing new businesses. Using data science techniques and tools, we analyze and compare different neighborhoods based on various factors.

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