About this document
Ciro Giuseppe de Vita, 2026 by nektaria.kokosia is a document available to read on EtoBox.
The document presents the AIQUAM++ model, an advanced AI-based framework designed to predict E. coli contamination in farmed mussels, addressing the limitations of traditional monitoring methods. It employs a combination of high-performance computing and machine learning techniques, including various Transformer architectures, to achieve over 90% classification accuracy in real-time predictions. The model is tested in the Gulf of Naples, demonstrating its potential as a decision-support tool for aquaculture
- Author
- nektaria.kokosia
- Language
- EN