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The aim of this study is to propose a bird detection algorithm. Bird detection is useful for the counting and dynamics of bird study. Neural networks are used for bird detection and the first step is to learn to classify bird species based on previous experiments. We further develop a proof of concept for the meta-data fusion which indicates that the fusion of elevation data can be used to increase the accuracy of the model, and to decrease its coverage error, in particular.

Automatic Identification of Flying Bird Species Using Computer Vision Technique for Ecological Data Analysis