Cancer Detector
For this project, I trained a CNN based on the UNET architecture on a database of labelled cancerous cell images. The goal was to predict cancer with >85% accuracy.
This is a conglomeration of various personal, class, or reaseach projects. Research projects often turn into papers so check out my publications page as well.
For this project, I trained a CNN based on the UNET architecture on a database of labelled cancerous cell images. The goal was to predict cancer with >85% accuracy.
Trained an RNN on State of the Union Adresses to predict sentences given a few letters.
Modeling, simulation, control, estimation, and path planning for a fixed wing UAV. The final result of the project is a simulator built from scratch with implementations of IMU, pressure, and GPS sensors, Extended Kalman Filter and RRT path planning.
This project uses SIFT feature matching and some computer vision techniques to automatically grade scantrons.
SIFT Feature extraction and detection for real-time image replacement.
Our team used a combination of computer vision, controls, and reinforcement learning to autonomously navigate a mini city. Our car is capable of recognizing and responding to signs, stopping at rail road crossings, and staying on the road.
Various implementations of localization and mapping algorithms.