LGF-CBAM vs. CBAM Model Performance on Cocoa Disease GH Dataset

Henry Techie-Menson published a performance comparison of the proposed LGF-CBAM model with baseline CBAM-based architectures on the Cocoa Disease GH dataset. The dataset is a 5.5 KB Excel file last updated on April 30, 2026. It is shared under a CC-BY-4.0 license on the figshare platform.

Use Cases

• Benchmarking convolutional neural network architectures based on the described performance metrics.
• Comparing the efficacy of attention mechanisms (CBAM, LGF-CBAM) for plant disease classification.
• Evaluating model performance on a specific agricultural dataset (Cocoa Disease GH).

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Has a clear, permissive license (CC-BY-4.0) for reuse.
• Provides a direct comparison of named model architectures (LGF-CBAM vs. CBAM).

Limitations

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

Provenance

Source

Henry Techie-Menson via figshare

Freshness

Last updated 2026-04-30 17:52:03; freshness should be verified.