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Classification of Animal Species Using a Deep Neural Network-Based Feature Extraction Method

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Date
2024
Author
Ibrahim, Mohammed, Al-Kubaise, Khamis, Alkapti, Ali, Almusa, Abdullah, Abdelaziz, Osama, Al-Maadeed, Somaya, Sadasivuni, Kishor Kumar
Collections
Computer Science & Engineering
Center for Advanced Materials Research
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Classification_of_Animal_Species_Using_a_Deep_Neural_Network-Based_Feature_Extraction_Method.pdf
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Abstract
This study presents an innovative approach to animal classification and recognition utilizing machine learning and deep learning methodologies. Leveraging advanced algorithms, the proposed system achieves remarkable accuracy in identifying diverse animal species. By integrating sophisticated image processing techniques, the system enhances image quality, improving overall performance. The research demonstrated that the SVM model combined with deep neural network-based feature extraction achieved the highest accuracy of 95.65%. This paper represents a significant stride toward improving the precision and efficiency of animal classification, offering promising applications in biodiversity conservation and ecological monitoring by using advanced feature extraction approach with deep learning.
URI
http://hdl.handle.net/10576/68974