Typhoon Intensity Classification Images from PTIT AI Challenge

A multi-class image classification dataset for tropical cyclone intensity estimation. The dataset originates from the PTIT AI Challenge and is structured with separate training and test sets. It was last updated on June 10, 2026, by the author star092304.

Use Cases

• Classifying typhoon intensity based on satellite or radar imagery mentioned in the description.
• Training machine learning models for automated storm analysis.
• Benchmarking image classification algorithms on a specialized meteorological task.

Strengths

• Dataset is structured for a specific multi-class image classification task.
• Separate training and test sets are provided for model evaluation.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

PTIT AI Challenge

Freshness

Last updated 2026-06-10 11:26:24; freshness should be verified.