Tropical Cyclone Identification and Alert System using AlexNet and Deep CNN
In one sentence. Uses an AlexNet-based CNN to identify tropical cyclones from aerial imagery for an alert system; a basic classification application.
Abstract
Tropical cyclones (TCs) are catastrophic weather occurrences that can inflict massive damage in coastal regions across the world. Weather nowcasting, which is the weather forecast for a short time period, is one of the most challenging topics in meteorology. Weather radar and satellite are essential technologies for nowcasting, but issuing nowcasting warnings based on radar and satellite data is a difficult process. This proposed approach is of a deep learning approach for TC identification from aerial imagery, which includes a Deep Convolutional Neural Network of Alex-Net architecture as the classifier.
Labels
- Topic
- Extremes & hazards, Nowcasting
- Type
- New model or method
- Method
- CNN / U-Net
- Time scale
- 0–6 h
- Domain
- Regional
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.36948/ijfmr.2023.v05i02.2581 OpenAlex:W4367189035
- Added
- 2026-10-22
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