Abstract
Simple SummaryMost parrot species are threatened with extinction because of habitat loss and commercial trade. Parrot conservation is vital because parrots play an important role in the ecosystem. The Amazon parrots are one of the most endangered parrot species. Monitoring their wild population and global trade is essential for their conservation. However, this is becoming more challenging because it requires manual analysis of large-scale image data. Furthermore, the morphological identification of the Amazon parrots can be difficult because they have similar morphological features. Deep learning-based object detection models are useful tools for monitoring wild populations and global trade. In this study, 26 Amazon parrot species were classified using eight object detection models. The object detection model, which showed the highest accuracy, classified the 26 Amazon parrot species at 90.7% on average. The continuous development of deep learning models for classifying Amazon parrots might help to improve the ability to monitor their wild populations and global trade.Parrots play a crucial role in the ecosystem by performing various roles, such as consuming the reproductive structures of plants and dispersing plant seeds. However, most are threatened because of habitat loss and commercial trade. Amazon parrots are one of the most traded and illegally traded parrots. Therefore, monitoring their wild populations and global trade is crucial for their conservation. However, monitoring wild populations is becoming more challenging because the manual analysis of large-scale datasets of images obtained from camera trap methods is labor-intensive and time consuming. Monitoring the wildlife trade is difficult because of the large quantities of wildlife trade. Amazon parrots can be difficult to identify because of their morphological similarity. Object detection models have been widely used for automatic and accurate species classification. In this study, to classify 26 Amazon parrot species, 8 Single Shot MultiBox Detector models were assessed. Among the eight models, the DenseNet121 model showed the highest mean average precision at 88.9%. This model classified the 26 Amazon parrot species at 90.7% on average. Continuous improvement of deep learning models classifying Amazon parrots may support monitoring wild populations and the global trade of these species.
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