Al-Jumaili, SaifAl-Jumaili, AhmedAlyassri, SalamDuru, Adil DenizUçan, Osman Nuri2022-12-232022-12-232022Al-jumaili, S., Al-jumaili, A., Alyassri, S., Duru, A. D., Uçan, O. N. (2022). Recent advances on convolutional architectures in medical applications: classical or quantum. In 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 800-805). IEEE.9781665470131https://hdl.handle.net/20.500.12939/3142Deep learning is one of the most significant advances in AI (AI). It is used in a variety of fields due to it has the ability to solve problems that cannot be handled by traditional technologies. The optimization of deep learning relevant to medical images is one of the most important recent advances in image analysis. Several developments have been done on Convolutional Neural Networks to achieve optimal accuracy and increase the learning speed. However, in this paper, we discuss the most recent innovations in convolutional neural networks within Classical method and Quantum method. We briefly provide a snapshot about the architecture, improvements, and principles of both (Classical and Quantum).eninfo:eu-repo/semantics/closedAccessClassificationConvolutional Neural NetworksDeep learningMedical imagesQuantum Convolutional Neural NetworksConference Object8008052-s2.0-85142832734N/A