A. Abasi

A Comparative Analysis of Feature-Based and Deep Learning Approaches for Image Classification

A unified and fully reproducible benchmarking framework that standardises preprocessing, enforces fixed train–test splits, aligns training configurations, and evaluates models using a consistent multi-metric suite is introduced, demonstrating that compute-aligned, multi-metric benchmarking is essential for fair and reproducible cross-paradigm evaluation.