Taxonomic Identification of European Seahorse H. Guttulatus and H. Hippocampus Based on Machine Learning Techniques

In recent years, machine learning (ML) algorithms have emerged as a powerful and innovative tool to enhance data processing and facilitate species identification across taxa, including birds, insects, and plants. Transfer learning can be used for classification, regression and clustering problems. This paper uses two trained models - VGG16 and ResNet50 - with Deep Convolutional Neural Networks for image recognition. We apply this methodology to Seahorse species recognition. The experimental results show that the average accuracy of VGG16 network can reach 91.7%.