A Birds Species Detection Utilizing an Effective Hybrid Model

The aim of this study is to improve the performance of detection Birds Species by proposed a hybrid model using a combination of MobileNetV2 for feature extraction, an Autoencoder for dimensionality reduction, and Support Vector Machines (SVM) for classification. The methodology includes preprocessing, augmentation, feature extraction, and classification phases. The proposed model is evaluated using the Bird Species dataset, consisting of 525 bird species the dataset is carefully curated to ensure cleanliness and absence of leakage between sets. The evaluation metrics include precision, recall, accuracy, and F-measure. The results have shown the efficiency of the proposed model in bird species classification.