Yamac, Senar AliKuyucuoglu, OrhunKoseoglu, Seyma BegumUlukaya, Sezer2024-06-122024-06-122022978-1-6654-6948-7https://doi.org/10.1109/TSP55681.2022.9851300https://hdl.handle.net/20.500.14551/2007645th International Conference on Telecommunications and Signal Processing (TSP) -- JUL 13-15, 2022 -- ELECTR NETWORKWhen the disorders that occur in the fingernails and toenails are not noticed early, they can turn into diseases that affect human life. These diseases in our hands and feet, which are mostly used organs in our daily work, also negatively affect the quality of life. In this study, it is aimed to detect 5 different nail diseases using deep learning architectures. Within the scope of the study, the performance of the 6 most recent deep learning architectures was compared with each other. Although the number of pictures in the open-access database used in the study is low, the obtained results seem to be successful.en10.1109/TSP55681.2022.9851300info:eu-repo/semantics/closedAccessConvolutional Neural Network (CNN)Data AugmentationNail DiseasesTelehealthTransfer LearningConference Object196199N/AWOS:0010708463000402-s2.0-85138085751N/A