3 ms·
Honestly, I think it's actually https://www.uber.com/en-CA/blog/h3/ https://www.uber.com/en-CA/blog/h3/
by fidotron 2y ago
Honestly, I think it's actually https://www.uber.com/en-CA/blog/h3/ https://www.uber.com/en-CA/blog/h3/
- jsemrau 2y agoMakes one wonder if the YOLO algorithm would work better with hexagons. "Hexagons were an important choice because people in a city are often in motion, and hexagons minimize the quantization error introduced when users move through a city. Hexagons also allow us to approximate radiuses easily, such as in this example using Elasticsearch." [Edit]Maybe https://www.researchgate.net/publication/372766828_YOLOv8_for_Defect_Inspection_of_Hexagonal_Directed_Self-Assembly_Patterns_A_Data-Centric_Approach https://www.researchgate.net/publication/372766828_YOLOv8_fo...
- sroerick 2y agoCould you elaborate on this? I experimented with h3 a bit for queries but I have never used it in production. Obviously, it's very effective for Uber but I wonder if you have any other experience with it