As a real-world application of image-based bird counting, we prepared the spatial bird order distribution and species diversity maps of Turkey by utilizing the geographic information system (GIS) technology. The experiments revealed that computer-aided counting outperformed the manual counting with respect to both accuracy and time. We employ several state-of-the-art generic object-detection algorithms to learn to detect birds, each being a member of one of the 38 identified species, in natural scenes. ![]() Our data source is a collection of on-ground photos taken during our long run of birding activity. For this purpose, we exploit the ability of computers to learn from past data through deep learning which has been a leading sub-field of AI for image understanding. A promising attempt towards solving the bird counting problem in a more consistent and fast way is to predict the number of birds in different regions from their photos. This necessitates the regular counting of birds which is usually not an easily-achievable task. Our results showed the potential of learning computers in support of real-world bird monitoring applications.Ī challenging problem in the field of avian ecology is deriving information on bird population movement trends. ![]() Finally, we used these counts to produce several bird distribution maps for further analysis. After a large collection of bird photos had been gathered, we predicted the bird counts in photo locations from images by making strong use of AI. The study has been practically initiated 10 years ago by beginning to take photos on a yearly basis in predefined regions of Turkey. Taking these uncertainties into account, we aimed at taking the advantage of the advances in the artificial intelligence (AI) field for a more standardized counting action. However, these methods can be expensive, time-consuming, and highly dependent on the mental and physical status of the observer and environmental factors. ![]() Traditional counting methods are widely used. This is vital for giving more precise management decisions and taking preventive actions when necessary. To detect changes in migrating bird populations that are usually gradual, regular counts of the flocks should be carried out.
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