diff --git a/README.md b/README.md
index d3f12c7..459bfc0 100755
--- a/README.md
+++ b/README.md
@@ -31,6 +31,11 @@ The models used for detection are SSD [SSD: Single Shot MultiBox Detector](https
 
 Grab the pretrained weights of SSD and  YOLO3 from [Drive_Weights](https://drive.google.com/drive/folders/1LSc9FkAwJrAAT8pAUWz8aax_biFAMMXS?usp=sharing)
 
+|    Model    |  Pretrained Weights |
+|:-----------:|:-------------------:|
+| SSD7/SSD300 |    [Weight VGG16](https://drive.google.com/open?id=1VHTx28tGI94yFqwT_WHp-xkx_8Hh_A31)|
+|    YOLO3    | [Weight Full Yolo3](https://drive.google.com/open?id=1cnCQHl-TnOrwb-leug1I0O9vMBaSwJLt)|
+
 ## Type of Data
 The images used for the design of this model were extracted by air analysis, specifically: FLIR aerial radiometric thermal infrared pictures, taken by UAV (R-JPEG format). Which were converted into .jpg images for the training of these detection models.
 Example FLIR image:
@@ -177,6 +182,15 @@ Compute the mAP performance of the model defined in `saved_weights_name` on the
 
 # Result
 All of weights of this trained model grab from [Drive_Weights](https://drive.google.com/drive/folders/1LSc9FkAwJrAAT8pAUWz8aax_biFAMMXS?usp=sharing)
+
+|      Model     | Pretrained Weights |  Config  |
+|:--------------:|:------------------:|:--------:|
+|   SSD7 Panel   |      [weight](https://drive.google.com/open?id=1qNjfAp9sW1VJh8ewnb3NKuafhZockTqV)      | [config](Result_ssd7_panel/config_7_panel.json) |
+| SSD300 Soiling |      [weight](https://drive.google.com/open?id=1IiOyYW8yPAh4IALbM_ZVqRhLdxV-ZSPw)      | [config](config_300_fault_1.json) |
+|   YOLO3 Panel  |      [weight](https://drive.google.com/open?id=14zgtgDJv3KTvhRC-VOz6sqsGPC_bdrL1)      | [config](config_full_yolo_panel_infer.json) |
+|  YOLO3 Soiling |      [weight](https://drive.google.com/open?id=1YLgkn1wL5xAGOpwd2gzdfsJVGYPzszn-)      | [config](config_full_yolo_fault_1_infer.json) |
+|   YOLO3 Diode  |      [weight](https://drive.google.com/open?id=1VUtrK9JVTbzBw5dX7_dgLTMToFHbAJl1)      | [config](config_full_yolo_fault_4_infer.json) |
+
 ## Panel Detector
 ### SDD7
 On folder [Result ssd7 panel](Result_ssd7_panel/) show code (jupyter notebook), weight and result of this model (mAP 89.8%).