Predicting Marine Microplastic Density via Spatiotemporal Deep Learning

This project predicts marine microplastic density given prediction parameters matched based on latitude, longitude, and time. The contrastive learning-based transformer is able to achieve a prediction accuracy of 82%. Users can contribute/get started with this project by modifying the transformer to improve prediction robustness.

This repository is created/maintained by Kayla Peng