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.