Deep Learning Model for Nanoparticle Detection

Project 42

Overview

We’re building an AI-based system to detect nanoparticles in microscopy images, aimed at accelerating research in material science and nanotech. The core is a custom Variational Autoencoder that spots and localizes particles without manual labels. It’s built in PyTorch with OpenCV for preprocessing, optimized to run efficiently for fast, scalable analysis of high-res image data.

 

Community Benefit

Helps researchers save time and reduce error in particle detection by replacing manual counting with an automated, reliable tool. Makes large-scale image analysis more accessible, speeding up discoveries in fields like drug delivery, electronics, and materials development.

 

Team Members

 

Sponsored By

Dr. KwangSoo Yang