# GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery

arXiv: https://arxiv.org/abs/1708.03417 · HTML: https://mlsanity.com/paper/1708.03417/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Aug 2017.

## Built on by (most cited first, 1 of 1)

- [Analysis of Object Detection Models for Tiny Object in Satellite Imagery: A Dataset-Centric Approach](https://mlsanity.com/paper/2412.10453/) (2024)

## Abstract (arXiv)

Advances in remote sensing technologies have made it possible to use high-resolution visual data for weather observation and forecasting tasks. We propose the use of multi-layer neural networks for understanding complex atmospheric dynamics based on multichannel satellite images. The capability of our model was evaluated by using a linear regression task for single typhoon coordinates prediction. A specific combination of models and different activation policies enabled us to obtain an interesting prediction result in the northeastern hemisphere (ENH).