Detection of fungal infection in dogs using deep learning techniques
Sunaina, Sukhpreet Kaur, Sukhdeep Kaur · Computational Methods in Science and Technology · 2024
Fungal infections at the skin of puppies, including dermatophytosis, are commonplace and pose great health dangers to each the animals and their proprietors. Although these infections do no longer affect human skin immediately, rapid detection remains important for well-timed remedy and spreading prevention. The currently established diagnosis process frequently includes the visual confirmation of the infection by medical professionals and fungal culture and is often referred to as time-intensive and highly dependent on medical professionals’ qualifications. Over the past few years, deep learning has become quite a promising area of research, R&D, and deployment in multiple fields, including medical imaging. The current research develops a deep learning model for fungal infection detection on the skin of dogs based on a variety of architectures and variations of Convolutional Neural Networks to classify image patches as healthy and infected. Transfer learning for the model structuring is reviewed to determine the impact of pre-trained models on the model&s;s learning efficiency.