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E-Moulouya BDD: Extended Moulouya Bird Detection Dataset
- Citation Author(s):
- Submitted by:
- Wiam RABHI
- Last updated:
- Mon, 07/31/2023 - 05:04
- DOI:
- 10.21227/es8y-cr94
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Abstract
The Extended Moulouya Bird Detection Dataset (E-Moulouya BDD) is a comprehensive collection of annotated images proposed for bird detection. The dataset is a combination of three datasets, namely the XMBA dataset, the Rest Birds Dataset, and the D-Birds Dataset, which were merged and cleaned up to provide a consistent and unified labeling format. The E-Moulouya BDD comprises 13,000 annotated images, labeled with a standardized format to ensure consistency across the dataset. The dataset is publicly available on IEEE DATAPORT, making it an ideal resource for use by the scientific community. The E-Moulouya BDD is a valuable addition to the existing bird detection datasets, and its availability is expected to facilitate and improve research in this field.
Please cite this work while using it for your projects by using:
W. Rabhi, F. Eljaimi, W. Amara, Z. Charouh, A. Ezzouhri, H. Benaboud, M. Saindou, and F. Ouardi, "An Integrated Framework for Bird Recog-nition using Dynamic Machine Learning-based Classification" in IEEE International Symposium on Computers and Communications, 2023.
Acknowledgments
We would like to express our sincere gratitude to the Moroccan Ministry of Energy Transition and Sustainable Development for its generous funding support for the E-Moulouya project. We are also deeply thankful to the Province of Berkane, the National Agency for Water and Forestry, the Berkane Prefectural Council, the Oriental Region Council, the Municipality of Saidia, the Moulouya Hydraulic Basin Agency, and the Man and Environment Association of Berkane for their invaluable insights, constructive discussions, and valuable feedback throughout the development of this project.
Comments
very helpful