GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery
Korea University of Science and Technology (UST)（韩国科学技术联合大学院大学）；Korea Institute of Science and Technology Information (KISTI)（韩国科学技术信息研究院）
英文摘要：
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).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
