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New AI technology could change game prep for Super Bowl teams: Study

New artificial intelligence technology being developed by engineers at Brigham Young University could significantly cut down on the time and cost that goes into film study for Super Bowl-bound teams (and all NFL and college football teams), while also enhancing game strategy by harnessing the power of big data. ....

Jacob Newman , Andrew Sumsion , Brigham Young University , Super Bowl Bound , Shad Torrie , Residual Network , Pistol Bunch , Formh Slot , Ews India ,

AI Tech Revolutionizes Super Bowl Team Prep

AI Tech Revolutionizes Super Bowl Team Prep
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.

United States , Jacob Newman , Andrew Sumsion , Brigham Young University , Vision Applications In Electronics , Philadelphia Eagles , Kansas City Chiefs , Super Bowl Bound , Shad Torrie , Residual Network , Pistol Bunch , Formh Slot , Pre Play Analysis , American Football Formations Using Deep Learning , Artificial Intelligence , Revision Applications ,

New AI technology could change game prep for Super Bowl teams

New AI technology could change game prep for Super Bowl teams
scienceblog.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from scienceblog.com Daily Mail and Mail on Sunday newspapers.

United States , Jacob Newman , Andrew Sumsion , Brigham Young University , Philadelphia Eagles , Kansas City Chiefs , Super Bowl Bound , Shad Torrie , Residual Network , Pistol Bunch , Formh Slot , Pre Play Analysis , American Football Formations Using Deep Learning , Artificial Intelligence , Revision Applications ,

"Artificial intelligence-enabled ECG algorithm based on improved residu" by Hongqiang Li, Zhixuan An et al.

Heart disease is the leading cause of death for men and women globally. The residual network (ResNet) evolution of electrocardiogram (ECG) technology has contributed to our under-standing of cardiac physiology. We propose an artificial intelligence-enabled ECG algorithm based on an improved ResNet for a wearable ECG. The system hardware consists of a wearable ECG with conductive fabric electrodes, a wireless ECG acquisition module, a mobile terminal App, and a cloud diagnostic platform. The algorithm adopted in this study is based on an improved ResNet for the rapid classification of different types of arrhythmia. First, we visualize ECG data and convert one-dimensional ECG signals into two-dimensional images using Gramian angular fields. Then, we improve the ResNet-50 network model, add multistage shortcut branches to the network, and optimize the residual block. The ReLu activation function is replaced by a scaled exponential linear units (SELUs) activation function to improve the ex ....

Biomedical Monitoring , Cloud Computing , Cg Science Popularization , Abric Electrodes , Residual Network ,