Endangered Specie

Research on endangered species is increasingly leveraging artificial intelligence to address challenges in monitoring, classification, and conservation. Current efforts focus on applying deep learning models, such as YOLOv8, ResNet, and various BERT variants, to analyze imagery (including drone footage) and textual data for species identification and population estimation, improving accuracy and efficiency compared to traditional methods. These advancements are crucial for enhancing conservation efforts by enabling more effective monitoring, habitat mapping, and ultimately, the protection of vulnerable species. The integration of genetic data with visual biometrics further refines species classification, particularly for rare species with limited image data.