AWPF-ResNet18 Mushroom Classification Model Performance Metrics

A 5.5 KB Excel file contains performance metrics for a deep learning model designed for mushroom classification. The AWPF-ResNet18 model, developed by Xinhai Zhao, achieved improvements in accuracy, precision, F1-score, and recall over a baseline model. The dataset was last updated on April 16, 2026.

Use Cases

• Benchmarking image classification models based on reported accuracy, precision, F1-score, and recall metrics
• Evaluating feature fusion techniques for mitigating semantic loss in downsampling
• Comparing model performance for tasks involving targets of varying sizes within images

Strengths

• Performance metrics are quantified with specific percentage improvements (e.g., accuracy increased by 2.5%)
• The model's effectiveness was validated through multiple comparative experiments

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• The dataset is very small (5.5 KB), indicating limited scope

Provenance

Source

figshare

Freshness

Last updated 2026-04-16 17:31:43; freshness should be verified