Enhancing crayfish sex identification with Kolmogorov-Arnold networks and stacked autoencoders
Scientific Reports, 16, Article 3971
DOI: 10.1038/s41598-025-34095-z
This study investigates crayfish sex identification using traditional machine learning, deep learning, Kolmogorov-Arnold networks, and autoencoder-based feature extraction. It highlights the potential of hybrid artificial intelligence models for biological classification problems.