Deep Learning-Based Automated Classification of Pathogenic Fungi from Microscopic Images using Enhanced EfficientNet-B4

The objective of this project is to develop an automated fungal classification system using Enhanced EfficientNet-B4 and Vision Transformer (ViT) with Learnable Spatial-Channel Attention (LSCA). The system classifies microscopic images into five fungal classes: Candida albicans, Aspergillus niger, Trichophyton rubrum, Trichophyton mentagrophytes, and Epidermophyton floccosum. It leverages federated learning and attention-based aggregation to improve accuracy, privacy, and robustness..”