1.What technologies are used by SSI? What is their purpose? High performance sports (HPS) analytics. The purpose of this technology is to gather video of athletes from practice and competitions to pinpoint and decencies that stand out.... more
1.What technologies are used by SSI? What is their purpose? High performance sports (HPS) analytics. The purpose of this technology is to gather video of athletes from practice and competitions to pinpoint and decencies that stand out. They are uploaded on a platform that can be accessed by athletes and coaches to breakdown. 3.Search the web for SimulCam and StroMotion. How can these tools be used for video analysis? These tools can be used to breakdown flaws in movements by an athlete and help pinpoint where the mistakes take place. StroMotion is an image enhancement tool that shows different frames of a recorded video, that can then be analyzed. Something a video can't do. SimulCam is used more in movies as a simulation and probably in video games to help bring a realistic image using simulations.
Implementing automated emotion recognition on mobile devices could provide an accessible diagnostic and therapeutic tool for those who struggle to recognize emotion, including children with developmental behavioral conditions such as... more
Implementing automated emotion recognition on mobile devices could provide an accessible diagnostic and therapeutic tool for those who struggle to recognize emotion, including children with developmental behavioral conditions such as autism. Although recent advances have been made in building more accurate emotion classifiers, existing models are too computationally expensive to be deployed on mobile devices. In this study, we optimized and profiled various machine learning models designed for inference on edge devices and were able to match previous state of the art results for emotion recognition on children. Our best model, a MobileNet-V2 network pre-trained on ImageNet, achieved 65.11% balanced accuracy and 64.19% F1-score on CAFE, while achieving a 45-millisecond inference latency on a Motorola Moto G6 phone. This balanced accuracy is only 1.79% less than the current state of the art for CAFE, which used a model that contains 26.62x more parameters and was unable to run on the ...