[docs] Delete compatibility matrix sections

docs/models/necks/fpn.md

@@ -4,35 +4,6 @@ FPN based on [Feature Pyramid Networks for Object Detection](https://openaccess.
 
 The Feature Pyramid Network (FPN) is designed to enhance feature maps given from the backbone, typically used for detection models. Therefore, we also recommend to use it in detection task as well. FPN can create more pyramid deeply than the input feature pyramid from backbone, and in such cases, additional convolution or pooling layers are added.
 
-## Compatibility matrix
-
-<table>
-  <tr>
-    <th>Supporting backbones</th>
-    <th>Supporting heads</th>
-    <th>torch.fx</th>
-    <th>NetsPresso</th>
-  </tr>
-  <tr>
-    <td>
-      ResNet<br />
-      MobileNetV3<br />
-      MixNet<br />
-      CSPDarkNet<br />
-      MobileViT<br />
-      MixTransformer<br />
-      EfficientFormer
-    </td>
-    <td>
-      ALLMLPDecoder<br />
-      AnchorDecoupledHead<br />
-      AnchorFreeDecoupledHead
-    </td>
-    <td>Supported</td>
-    <td>Supported</td>
-  </tr>
-</table>
-
 ## Field list
 
 | Field <img width=200/> | Description |

docs/models/necks/rtdetrhybridencoder.md

@@ -3,34 +3,6 @@
 RT-DETR Hybrid Encoder based on [RT-DETR: DETRs Beat YOLOs on Real-time Object Detection](https://arxiv.org/abs/2304.08069)
 
 
-## Compatibility matrix
-
-<table>
-  <tr>
-    <th>Supporting backbones</th>
-    <th>Supporting heads</th>
-    <th>torch.fx</th>
-    <th>NetsPresso</th>
-  </tr>
-  <tr>
-    <td>
-      ResNet<br />
-      MobileNetV3<br />
-      MobileNetV4<br />
-      MixNet<br />
-      CSPDarkNet<br />
-      MobileViT<br />
-      MixTransformer<br />
-      EfficientFormer
-    </td>
-    <td>
-      RT-DETR head 
-    </td>
-    <td>Supported</td>
-    <td>Not Supported</td>
-  </tr>
-</table>
-
 
 ## Field lists
 | Field <img width=200/> | Description |

docs/models/necks/yolopafpn.md

@@ -4,35 +4,6 @@ YOLOPAFPN based on [YOLOX: Exceeding YOLO Series in 2021](https://arxiv.org/abs/
 
 YOLOPAFPN is a modified PAFPN for YOLOX model. Therefore, although YOLOPAFP is compatible with various backbones, we recommend to use it when constructing YOLOX models. The size is determined by `dep_mul` value, which defines the repetition of CSPLayers.
 
-## Compatibility matrix
-
-<table>
-  <tr>
-    <th>Supporting backbones</th>
-    <th>Supporting heads</th>
-    <th>torch.fx</th>
-    <th>NetsPresso</th>
-  </tr>
-  <tr>
-    <td>
-      ResNet<br />
-      MobileNetV3<br />
-      MixNet<br />
-      CSPDarkNet<br />
-      MobileViT<br />
-      MixTransformer<br />
-      EfficientFormer
-    </td>
-    <td>
-      ALLMLPDecoder<br />
-      AnchorDecoupledHead<br />
-      AnchorFreeDecoupledHead
-    </td>
-    <td>Supported</td>
-    <td>Supported</td>
-  </tr>
-</table>
-
 ## Field list
 
 | Field <img width=200/> | Description |