diff --git a/src/demo.c b/src/demo.c
index 2337a0ad..6ae3c336 100644
--- a/src/demo.c
+++ b/src/demo.c
@@ -148,7 +148,7 @@ void demo(char *cfgfile, char *weightfile, float thresh, float hier_thresh, int
         load_weights(&net, weightfile);
     }
     set_batch_network(&net, 1);
-
+	fuse_conv_batchnorm(net);
     srand(2222222);
 
     if(filename){
diff --git a/src/detector.c b/src/detector.c
index 45d3b226..25968e66 100644
--- a/src/detector.c
+++ b/src/detector.c
@@ -419,6 +419,7 @@ void validate_detector_recall(char *datacfg, char *cfgfile, char *weightfile)
 		load_weights(&net, weightfile);
 	}
 	set_batch_network(&net, 1);
+	fuse_conv_batchnorm(net);
 	srand(time(0));
 
 	//list *plist = get_paths("data/coco_val_5k.list");
@@ -526,6 +527,7 @@ void validate_detector_map(char *datacfg, char *cfgfile, char *weightfile, float
 		load_weights(&net, weightfile);
 	}
 	set_batch_network(&net, 1);
+	fuse_conv_batchnorm(net);
 	srand(time(0));
 
 	list *plist = get_paths(valid_images);
@@ -1022,6 +1024,7 @@ void test_detector(char *datacfg, char *cfgfile, char *weightfile, char *filenam
         load_weights(&net, weightfile);
     }
     set_batch_network(&net, 1);
+	fuse_conv_batchnorm(net);
     srand(2222222);
     clock_t time;
     char buff[256];
diff --git a/src/network.c b/src/network.c
index 175c1029..bfade3cc 100644
--- a/src/network.c
+++ b/src/network.c
@@ -748,3 +748,38 @@ void free_network(network net)
 	free(net.workspace);
 #endif
 }
+
+
+void fuse_conv_batchnorm(network net)
+{
+	int j;
+	for (j = 0; j < net.n; ++j) {
+		layer *l = &net.layers[j];
+
+		if (l->type == CONVOLUTIONAL) {
+			printf(" Fuse Convolutional layer \t\t l->size = %d  \n", l->size);
+
+			if (l->batch_normalize) {
+				int f;
+				for (f = 0; f < l->n; ++f)
+				{
+					l->biases[f] = l->biases[f] - l->scales[f] * l->rolling_mean[f] / (sqrtf(l->rolling_variance[f]) + .000001f);
+
+					const size_t filter_size = l->size*l->size*l->c;
+					int i;
+					for (i = 0; i < filter_size; ++i) {
+						int w_index = f*filter_size + i;
+
+						l->weights[w_index] = l->weights[w_index] * l->scales[f] / (sqrtf(l->rolling_variance[f]) + .000001f);
+					}
+				}
+
+				l->batch_normalize = 0;
+				push_convolutional_layer(*l);
+			}
+		}
+		else {
+			printf(" Skip layer: %d \n", l->type);
+		}
+	}
+}
diff --git a/src/network.h b/src/network.h
index 5b405c4a..965693ad 100644
--- a/src/network.h
+++ b/src/network.h
@@ -138,6 +138,7 @@ void free_detections(detection *dets, int n);
 
 int get_network_nuisance(network net);
 int get_network_background(network net);
+void fuse_conv_batchnorm(network net);
 
 #ifdef __cplusplus
 }