A comprehensive feature fusion method for detecting pork adulteration in beef using CNN-GRU-LSTM networks

Key Points

• Detection accuracy improved through feature fusion techniques, demonstrating superior performance.
• CNN, GRU, and LSTM networks were employed to analyze beef samples with pork adulteration.
• Assessment utilized a dataset of mixed meat samples, enhancing detection capabilities across varied conditions.
• Findings suggest that advanced network architectures may significantly enhance food safety measures.