Abstract
Given its location on the migration route of the Western Palearctic, the complex of wetlands of El-Kala (North-East Algeria) forms the most important and diverse area of the Mediterranean for migratory birds in the Maghreb. The knowledge of these birds allows one to acquire crucial information on the state of health of considered environments as well as annual statistics of this population. Some of which are threatened with extinction. Because of the dense vegetation, the main feature characterizing the birds' habitat, the identification of bird species from their images is made a complicated task. In addition, there is a high degree of similarity between classes and features. In this paper and in order to solve these problems, a new method named DarkBirdNet based on deep learning has been developed. This method is derived from the predefined DarkNet53 model and aims at detecting and classifying bird species in Algeria.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Sociotechnology and Knowledge Development
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
