Perpetuini, D.; Formenti, D.; Cardone, D.; Trecroci, A.; Rossi, A.; Di Credico, A.; Merati, G.; Alberti, G.; Di Baldassarre, A.; Merla, A.
Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue? Sensors 2023, 23, 832.
https://doi.org/10.3390/s23020832
AMA Style
Perpetuini D, Formenti D, Cardone D, Trecroci A, Rossi A, Di Credico A, Merati G, Alberti G, Di Baldassarre A, Merla A.
Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue? Sensors. 2023; 23(2):832.
https://doi.org/10.3390/s23020832
Chicago/Turabian Style
Perpetuini, David, Damiano Formenti, Daniela Cardone, Athos Trecroci, Alessio Rossi, Andrea Di Credico, Giampiero Merati, Giampietro Alberti, Angela Di Baldassarre, and Arcangelo Merla.
2023. "Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue?" Sensors 23, no. 2: 832.
https://doi.org/10.3390/s23020832
APA Style
Perpetuini, D., Formenti, D., Cardone, D., Trecroci, A., Rossi, A., Di Credico, A., Merati, G., Alberti, G., Di Baldassarre, A., & Merla, A.
(2023). Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue? Sensors, 23(2), 832.
https://doi.org/10.3390/s23020832