Implementation of artificial intellect for bird pest species detection and monitoring

Implementation of artificial intellect for bird pest species detection and monitoring

Blog Article

This NADH study aimed to develop a real-time method for detecting and selecting birds in video images using artificial intelligence.The objectives included creating a reliable method for isolating bird signals against varying terrain backgrounds using neural networks, estimating bird numbers in frames through AI-driven threshold techniques, and proposing a solution for managing pest bird populations by analyzing video data to control electronic deterrents.Throughout the research, we identified the bird species present on the premises of brewery Ski de fond - Homme - Vetements - Chandail across different seasons, compiled an annotated species list, and established a database of granary birds.Leveraging the YOLO architecture based on artificial intelligence, we developed a program for bird detection in low-resolution, low-quality images.The system underwent laboratory and field testing to validate its effectiveness.