Automatic bird identification for offshore wind farms: A case study for deep learning

An automatic bird identification system is required for offshore wind farms in Finland. Indubitably, a radar is the obvious choice to detect birds but actual identification requires external information such as digital images. The final bird species identification is based on a fusion of radar data and image data. We applied deep learning method for image classification and we developed a data expansion technique for the training data. We present classification results for the image classifier based on small convolutional neural network.