GarcÃa GarvÃ, A.;                     Puchalt, J.C.;                     Layana Castro, P.E.;                     Navarro Moya, F.;                     Sánchez-Salmerón, A.-J.    
        Towards Lifespan Automation for Caenorhabditis elegans Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification. Sensors 2021, 21, 4943.
    https://doi.org/10.3390/s21144943
    AMA Style
    
                                GarcÃa Garvà A,                                 Puchalt JC,                                 Layana Castro PE,                                 Navarro Moya F,                                 Sánchez-Salmerón A-J.        
                Towards Lifespan Automation for Caenorhabditis elegans Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification. Sensors. 2021; 21(14):4943.
        https://doi.org/10.3390/s21144943
    
    Chicago/Turabian Style
    
                                GarcÃa GarvÃ, Antonio,                                 Joan Carles Puchalt,                                 Pablo E. Layana Castro,                                 Francisco Navarro Moya,                                 and Antonio-José Sánchez-Salmerón.        
                2021. "Towards Lifespan Automation for Caenorhabditis elegans Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification" Sensors 21, no. 14: 4943.
        https://doi.org/10.3390/s21144943
    
    APA Style
    
                                GarcÃa GarvÃ, A.,                                 Puchalt, J. C.,                                 Layana Castro, P. E.,                                 Navarro Moya, F.,                                 & Sánchez-Salmerón, A.-J.        
        
        (2021). Towards Lifespan Automation for Caenorhabditis elegans Based on Deep Learning: Analysing Convolutional and Recurrent Neural Networks for Dead or Live Classification. Sensors, 21(14), 4943.
        https://doi.org/10.3390/s21144943