diff --git a/dbnet/common.hpp b/dbnet/common.hpp
index b1286de..e26aebc 100644
--- a/dbnet/common.hpp
+++ b/dbnet/common.hpp
@@ -110,8 +110,8 @@ ILayer* convBnLeaky(INetworkDefinition *network, std::map<std::string, Weights>&
     conv1->setPaddingNd(DimsHW{ p, p });
     conv1->setNbGroups(g);
     //IScaleLayer* bn1 = addBatchNorm2d(network, weightMap, *conv1->getOutput(0), lname + ".bn", 1e-4);
-    IScaleLayer* bn1 = addBatchNorm2d(network, weightMap, *conv1->getOutput(0), lname.substr(0, lname.find_last_of(".")) + bnname, 1e-3);
-    auto lr = network->addActivation(*bn1->getOutput(0), ActivationType::kLEAKY_RELU);
+    IScaleLayer* bn1 = addBatchNorm2d(network, weightMap, *conv1->getOutput(0), lname.substr(0, lname.find_last_of(".")) + bnname, 1e-5);
+    auto lr = network->addActivation(*bn1->getOutput(0), ActivationType::kRELU);
     lr->setAlpha(0.1);
     return lr;
 }
diff --git a/hrnet/hrnet-semantic-segmentation/README.md b/hrnet/hrnet-semantic-segmentation/README.md
index 70acf01..ccf6591 100644
--- a/hrnet/hrnet-semantic-segmentation/README.md
+++ b/hrnet/hrnet-semantic-segmentation/README.md
@@ -1,13 +1,13 @@
 # HRNet-Semantic-Segmentation
 
-The Pytorch implementation is [HRNet-Semantic-Segmentation](https://github.com/HRNet/HRNet-Semantic-Segmentation).  The implemented model is **HRNetV2-W18-Small-v2**
+The Pytorch implementation is [HRNet-Semantic-Segmentation-v1.1](https://github.com/HRNet/HRNet-Semantic-Segmentation/tree/pytorch-v1.1).  The implemented model is **HRNetV2-W18-Small-v2**
 
 
 ## How to Run
 
 * 1. generate .wts
 
-  Download code and model from [HRNet-Semantic-Segmentation](https://github.com/HRNet/HRNet-Semantic-Segmentation) and config your environments.
+  Download code and model from [HRNet-Semantic-Segmentation-v1.1](https://github.com/HRNet/HRNet-Semantic-Segmentation/tree/pytorch-v1.1) and config your environments.
 
   Put `demo.py`  in the `YOUR_ROOT_DIR\HRNet-Semantic-Segmentation\tools `  folder, set `savewts in  main()` as `True`, and run, the .wts will be generated.