Update README.md

README.md

@@ -26,10 +26,10 @@ VanillaNet, in its robust simplicity, offers comparable precision to prevalent c
 | Framework | Backbone | FLOPs(G) | #params(M) | FPS | AP<sup>b</sup> | AP<sup>m</sup> |
 |:---:|:---:|:---:|:---:| :---:|:---:|:---:|
 | RetinaNet | Swin-T | 245 | 38.5 | 27.5 | 41.5 | - |
-|  | VanillaNet-13 | 386 | 67.0 | 30.4 | 41.8 | - |
+|  | VanillaNet-11 | 386 | 67.0 | 30.8 | 41.8 | - |
 | Mask RCNN | ConvNeXtV2-N | 221 | 35.2 | 31.7 | 42.7 | 38.9 |
 |  | [Swin-T](https://github.com/open-mmlab/mmdetection/tree/main/configs/swin) | 267 | 47.8 | 28.2 | 42.7 | 39.3 |
-|  | VanillaNet-13 | 404 | 107.5 | 33.2 | 42.9 | 39.6 |
+|  | VanillaNet-11 | 404 | 107.5 | 33.6 | 42.9 | 39.6 |
 
 VanillaNet achieves a higher Frames Per Second (FPS) in **detection** and **segmentation** tasks.