INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Dog breed classification has practical applications such as animal care, veterinary medicine, and human-animal interactions. we introduce an approach for classifying dog breeds in images using the Xception Architecture, the deep learning model, developed in Python, achieved a notable training accuracy of 91.34% and a validation accuracy of 89.45%. This was made possible through the use of the Xception Architecture and a carefully curated dataset comprising 7515 dog images representing 133 diverse dog breed classifications.Leveraging this dataset, our model demonstrates exceptional generalization and robustness, effectively distinguishing between various dog breeds. The Xception Architecture enables feature extraction and representation, allowing our model to discern subtle patterns and features within the images, contributing to its outstanding classification performance.
The utilization of this architecture ensures that our model efficiently learns from the dataset and captures the subtle nuances that differentiate one dog breed from another. The attained results exemplify the effectiveness of our approach in tackling the challenging task of dog breed classification. The high training and validation accuracies demonstrate the model's ability to learn and generalize effectively.
Our Dog Breed Classification system presents a advancement in the domain of image classification using deep learning, showcasing the potential of the Xception Architecture for solving intricate real-world problems. The obtained results underscore the importance of utilizing sophisticated deep learning techniques and carefully curated datasets to achieve great performance in breed recognition tasks, with applications in animal welfare, veterinary science, and etc.
Keywords:
Dog Breed Classification, Xception Architecture, Convolutional Neural Networks, Deep Learning.
Cite Article:
"DOG BREED CLASSIFICATION USING XCEPTION ARCHITECTURE", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.g471-g479, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403658.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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