Scrutiny of Methods for Image Detection and Recognition of Different Species of Animals
Elham Mohammed Thabit A. Alsadi1, Nidhal K. El Abbadi2
1Elham Mohammed Thabit A. Alsadi, College of Information Technology, University of Babylon, Iraq.
2Nidhal K. El Abbadi, Education College, University of Kufa, Iraq.
Manuscript received on 24 November 2019 | Revised Manuscript received on 05 December 2019 | Manuscript Published on 16 December 2019 | PP: 151-160 | Volume-8 Issue-3S3 November 2019 | Retrieval Number: C10461183S319/2019©BEIESP | DOI: 10.35940/ijrte.C1046.1183S319
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Animal detection-based study is useful in many real-life applications. Techniques involved in animal detection are useful in observing the locomotive behavior of the engaged animal and in result it prevent harmful interruption of animals in residential areas. There are some branches of research in animal detection. Some of these branches will therefore be discussed in this journal. Humans have developed many algorithms and techniques to gain a better understanding of animal behaviour. Therefore, for early preventive measures, these technologies can also serve as a warning system for humans from encroachment of dangerous wild animals. Such tasks can be reduced to three main branches, namely animal detection, tracking and recognition. Through these papers, new approaches for study and a variety of technologies/algorithms implemented in the past are identified and appropriate ways for solving the research gaps are suggested to fill the gap.
Keywords: Deep Learning, Deep Neural Networks, Artificial Intelligence, Camera-Trap Images, Animal Detection & Recognition.
Scope of the Article: Signal and Image Processing