A Review of Machine Learning Approaches for Canine Skin Disease Detection Using Image Processing Techniques
Abstract
This literature review explores recent advancements in machine learning and image processing techniques for the detection of canine skin diseases. Sixteen studies were analyzed, focusing on different methodologies such as convolutional neural networks (CNNs), support vector machines (SVMs), and deep learning frameworks. The review highlights the applications, advantages, and limitations of these approaches in terms of accuracy, efficiency, and applicability. This work aims to provide insights into the current state of research and identify potential areas for future exploration.
Keywords:
SVM, Canine skin disease detection, image processing, artificial neural network, machine learning, deep learning, CNN
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Copyright (c) 2024 International Journal on Emerging Research Areas
This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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