Toofanee, M.S.A.;                     Hamroun, M.;                     Dowlut, S.;                     Tamine, K.;                     Petit, V.;                     Duong, A.K.;                     Sauveron, D.    
        Federated Learning: Centralized and P2P for a Siamese Deep Learning Model for Diabetes Foot Ulcer Classification. Appl. Sci. 2023, 13, 12776.
    https://doi.org/10.3390/app132312776
    AMA Style
    
                                Toofanee MSA,                                 Hamroun M,                                 Dowlut S,                                 Tamine K,                                 Petit V,                                 Duong AK,                                 Sauveron D.        
                Federated Learning: Centralized and P2P for a Siamese Deep Learning Model for Diabetes Foot Ulcer Classification. Applied Sciences. 2023; 13(23):12776.
        https://doi.org/10.3390/app132312776
    
    Chicago/Turabian Style
    
                                Toofanee, Mohammud Shaad Ally,                                 Mohamed Hamroun,                                 Sabeena Dowlut,                                 Karim Tamine,                                 Vincent Petit,                                 Anh Kiet Duong,                                 and Damien Sauveron.        
                2023. "Federated Learning: Centralized and P2P for a Siamese Deep Learning Model for Diabetes Foot Ulcer Classification" Applied Sciences 13, no. 23: 12776.
        https://doi.org/10.3390/app132312776
    
    APA Style
    
                                Toofanee, M. S. A.,                                 Hamroun, M.,                                 Dowlut, S.,                                 Tamine, K.,                                 Petit, V.,                                 Duong, A. K.,                                 & Sauveron, D.        
        
        (2023). Federated Learning: Centralized and P2P for a Siamese Deep Learning Model for Diabetes Foot Ulcer Classification. Applied Sciences, 13(23), 12776.
        https://doi.org/10.3390/app132312776