Title: GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery,
Abstract: 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).