Deep learning–based automatic bird identification system for offshore wind farms
Tutkimustuotos › › vertaisarvioitu
|DOI - pysyväislinkit|
|Tila||Julkaistu - 2020|
In the proposed system, a separate radar system detects birds and provides WGS84 coordinates to a steering system of a camera. The steering system consists of a motorized video head and our software to control it. The steering system tracks flying birds in order to capture series of images by a digital single-lens reflex camera. Classification is based on these images, and it is implemented by convolutional neural network trained with a deep learning algorithm. We applied to the images our data augmentation method, in which images are rotated and converted into different color temperatures. The results indicate that the proposed system has good performance to identify bird species in the test area. Aiming accuracy for the video head was 88.91 %. Image classification performance as true positive rate was 0.8688.