A Novel Deep Learning Model for Recognition of Endangered Water-Bird Species

Author:

Redjati Abdelghani1,Boulmaiz Amira1,Boughazi Mohamed1,Boukari Karima1ORCID,Meghni Billel1

Affiliation:

1. University of Badji Mokhtar, Annaba, Algeria

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.

Publisher

IGI Global

Subject

Information Systems and Management,Computer Science Applications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Confronting Current Crises and Critical Challenges of Climate Change;International Journal of Sociotechnology and Knowledge Development;2023-03-03

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3