Difference between revisions of "Sports"
m (→Baseball - Stealing Signs) |
m |
||
| Line 13: | Line 13: | ||
* [http://www.sas.com/en_us/customers/scisports.html Dutch sports analytics company SciSports uses emerging tech to innovate on the pitch | SAS] | * [http://www.sas.com/en_us/customers/scisports.html Dutch sports analytics company SciSports uses emerging tech to innovate on the pitch | SAS] | ||
* [http://www.forbes.com/sites/stevemccaskill/2019/01/31/ai-is-changing-the-face-of-golf-club-design/#4cd46557f836 AI Is Changing The Face Of Golf Club Design | Steve McCaskill] | * [http://www.forbes.com/sites/stevemccaskill/2019/01/31/ai-is-changing-the-face-of-golf-club-design/#4cd46557f836 AI Is Changing The Face Of Golf Club Design | Steve McCaskill] | ||
| + | * [http://www.npr.org/2022/07/07/1110338570/fifa-to-install-ai-to-help-make-accurate-offside-decisions#:~:text=The%20organization%20says%20it%20will,accurate%20decisions%20happen%20more%20quickly FIFA to install AI to help make accurate offside decisions | Juana Summers - NPR] | ||
<youtube>oMx6Q3YKxXM</youtube> | <youtube>oMx6Q3YKxXM</youtube> | ||
Revision as of 19:06, 8 July 2022
Youtube search... ...Google search
- Case Studies
- Dutch sports analytics company SciSports uses emerging tech to innovate on the pitch | SAS
- AI Is Changing The Face Of Golf Club Design | Steve McCaskill
- FIFA to install AI to help make accurate offside decisions | Juana Summers - NPR
Baseball Analytics
Baseball - Stealing Signs
|
Skeletal Motion
Fujitsu’s AI Gymnastics: The joint recognition module uses deep learning technology. The neural network model receives several multi-viewpoint depth images as input and outputs corresponding 3D joint position results. Joint recognition also requires certain adjustments and calibrations according to the human joint model, however the method behind this has not been published. A Fujitsu researcher told Synced his team worked closely with the Japanese Gymnastics Association to build up the database with a set of elements for each skill difficulty. They collected over 800 elements for male gymnasts and more than 500 elements for female gymnasts — where the elements comprise a series of basic skills from top gymnasts. Again, details on the procedure and the possible use of deep learning remain cloaked in mystery. Meet Fujitsu’s AI Gymnastics Judges