Morilla, F.; Vega, J.; Dormido-Canto, S.; Romero-Maestre, A.; de-MartÃn-Hernández, J.; Morilla, Y.; MartÃn-Holgado, P.; DomÃnguez, M.
A Machine Learning Approach to Predict Radiation Effects in Microelectronic Components. Sensors 2024, 24, 4276.
https://doi.org/10.3390/s24134276
AMA Style
Morilla F, Vega J, Dormido-Canto S, Romero-Maestre A, de-MartÃn-Hernández J, Morilla Y, MartÃn-Holgado P, DomÃnguez M.
A Machine Learning Approach to Predict Radiation Effects in Microelectronic Components. Sensors. 2024; 24(13):4276.
https://doi.org/10.3390/s24134276
Chicago/Turabian Style
Morilla, Fernando, Jesús Vega, Sebastián Dormido-Canto, Amor Romero-Maestre, José de-MartÃn-Hernández, Yolanda Morilla, Pedro MartÃn-Holgado, and Manuel DomÃnguez.
2024. "A Machine Learning Approach to Predict Radiation Effects in Microelectronic Components" Sensors 24, no. 13: 4276.
https://doi.org/10.3390/s24134276
APA Style
Morilla, F., Vega, J., Dormido-Canto, S., Romero-Maestre, A., de-MartÃn-Hernández, J., Morilla, Y., MartÃn-Holgado, P., & DomÃnguez, M.
(2024). A Machine Learning Approach to Predict Radiation Effects in Microelectronic Components. Sensors, 24(13), 4276.
https://doi.org/10.3390/s24134276
