Dataset and Pre-trained Models for: A Bio-Consistent Hierarchical Cascade Network (BCHCN) for Bacterial Classification

This repository contains the essential dataset and pre-trained model weights required to reproduce the Bio-Consistent Hierarchical Cascade Network (BCHCN) proposed for automated bacterial classification. Contents: data.zip: Contains the hierarchical patch-level microscopy images utilized for training and evaluation. The data is structured to support multi-scale inference, specifically aligned for Gram staining, morphological feature extraction, and species-level identification tasks. models.zip: Contains the optimized ResNet-50 backbone weights for the three distinct hierarchical stages: Stage 1 (Gram constraint), Stage 2 (Morphological constraint), and Stage 3 (Species identification). These resources are designed to be used in conjunction with the official GitHub repository associated with the manuscript, ensuring full reproducibility of the double-masking clinical safety evaluations and Grad-CAM feature attributions.