diff --git a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app.cpp b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app.cpp
index 7e0786260..18e2de6dd 100644
--- a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app.cpp
+++ b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app.cpp
@@ -230,7 +230,8 @@ int main(int argc, char* argv[])
     std::cout << "Number of Input Nodes: " << numInputNodes << std::endl;
     std::cout << "Number of Output Nodes: " << numOutputNodes << std::endl;
 
-    const char* inputName = session.GetInputName(0, allocator);
+    auto inputNodeName = session.GetInputNameAllocated(0, allocator);
+    const char* inputName = inputNodeName.get();
     std::cout << "Input Name: " << inputName << std::endl;
 
     Ort::TypeInfo inputTypeInfo = session.GetInputTypeInfo(0);
@@ -242,7 +243,8 @@ int main(int argc, char* argv[])
     std::vector<int64_t> inputDims = inputTensorInfo.GetShape();
     std::cout << "Input Dimensions: " << inputDims << std::endl;
 
-    const char* outputName = session.GetOutputName(0, allocator);
+    auto outputNodeName = session.GetOutputNameAllocated(0, allocator);
+    const char* outputName = outputNodeName.get();
     std::cout << "Output Name: " << outputName << std::endl;
 
     Ort::TypeInfo outputTypeInfo = session.GetOutputTypeInfo(0);
diff --git a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app_io.cpp b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app_io.cpp
index c0642d03f..ec84669d6 100644
--- a/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app_io.cpp
+++ b/c_cxx/OpenVINO_EP/Linux/squeezenet_classification/squeezenet_cpp_app_io.cpp
@@ -1,6 +1,7 @@
 /*
 Copyright (C) 2021, Intel Corporation
 SPDX-License-Identifier: Apache-2.0
+
 Portions of this software are copyright of their respective authors and released under the MIT license:
 - ONNX-Runtime-Inference, Copyright 2020 Lei Mao. For licensing see https://github.com/leimao/ONNX-Runtime-Inference/blob/main/LICENSE.md
 */
@@ -260,7 +261,8 @@ int main(int argc, char* argv[])
     std::cout << "Number of Input Nodes: " << numInputNodes << std::endl;
     std::cout << "Number of Output Nodes: " << numOutputNodes << std::endl;
 
-    const char* inputName = session.GetInputName(0, allocator);
+    auto inputNodeName = session.GetInputNameAllocated(0, allocator);
+    const char* inputName = inputNodeName.get();
     std::cout << "Input Name: " << inputName << std::endl;
 
     Ort::TypeInfo inputTypeInfo = session.GetInputTypeInfo(0);
@@ -272,7 +274,8 @@ int main(int argc, char* argv[])
     std::vector<int64_t> inputDims = inputTensorInfo.GetShape();
     std::cout << "Input Dimensions: " << inputDims << std::endl;
 
-    const char* outputName = session.GetOutputName(0, allocator);
+    auto outputNodeName = session.GetOutputNameAllocated(0, allocator);
+    const char* outputName = outputNodeName.get();
     std::cout << "Output Name: " << outputName << std::endl;
 
     Ort::TypeInfo outputTypeInfo = session.GetOutputTypeInfo(0);
diff --git a/c_cxx/OpenVINO_EP/Windows/squeezenet_classification/squeezenet_cpp_app.cpp b/c_cxx/OpenVINO_EP/Windows/squeezenet_classification/squeezenet_cpp_app.cpp
index fe1a70a66..3349494ca 100644
--- a/c_cxx/OpenVINO_EP/Windows/squeezenet_classification/squeezenet_cpp_app.cpp
+++ b/c_cxx/OpenVINO_EP/Windows/squeezenet_classification/squeezenet_cpp_app.cpp
@@ -235,7 +235,8 @@ int main(int argc, char* argv[])
     std::cout << "Number of Input Nodes: " << numInputNodes << std::endl;
     std::cout << "Number of Output Nodes: " << numOutputNodes << std::endl;
 
-    const char* inputName = session.GetInputName(0, allocator);
+    auto inputNodeName = session.GetInputNameAllocated(0, allocator);
+    const char* inputName = inputNodeName.get();
     std::cout << "Input Name: " << inputName << std::endl;
 
     Ort::TypeInfo inputTypeInfo = session.GetInputTypeInfo(0);
@@ -247,7 +248,8 @@ int main(int argc, char* argv[])
     std::vector<int64_t> inputDims = inputTensorInfo.GetShape();
     std::cout << "Input Dimensions: " << inputDims << std::endl;
 
-    const char* outputName = session.GetOutputName(0, allocator);
+    auto outputNodeName = session.GetOutputNameAllocated(0, allocator);
+    const char* outputName = outputNodeName.get();
     std::cout << "Output Name: " << outputName << std::endl;
 
     Ort::TypeInfo outputTypeInfo = session.GetOutputTypeInfo(0);
diff --git a/c_sharp/OpenVINO_EP/yolov3_object_detection/Program.cs b/c_sharp/OpenVINO_EP/yolov3_object_detection/Program.cs
index 8ac757e1c..cdddc5628 100644
--- a/c_sharp/OpenVINO_EP/yolov3_object_detection/Program.cs
+++ b/c_sharp/OpenVINO_EP/yolov3_object_detection/Program.cs
@@ -133,17 +133,20 @@ static void Main(string[] args)
             for (int i = 0; i < indices.Length; i = i + 3)
             {
                 out_classes[count] = indices[i + 1];
-                out_scores[count] = scores[indices[i], indices[i + 1], indices[i + 2]];
-                predictions.Add(new Prediction
+                if (indices[i + 1] > -1)
                 {
-                       Box = new Box(boxes[indices[i], indices[i + 2], 1],
-                                     boxes[indices[i], indices[i + 2], 0],
-                                     boxes[indices[i], indices[i + 2], 3],
-                                     boxes[indices[i], indices[i + 2], 2]),
-                        Class = LabelMap.Labels[out_classes[count]],
-                        Score = out_scores[count]
-                });
-                count++;
+                    out_scores[count] = scores[indices[i], indices[i + 1], indices[i + 2]];
+                    predictions.Add(new Prediction
+                    {
+                        Box = new Box(boxes[indices[i], indices[i + 2], 1],
+                                        boxes[indices[i], indices[i + 2], 0],
+                                        boxes[indices[i], indices[i + 2], 3],
+                                        boxes[indices[i], indices[i + 2], 2]),
+                            Class = LabelMap.Labels[out_classes[count]],
+                            Score = out_scores[count]
+                    });
+                    count++;
+                }
             }
 
             // Put boxes, labels and confidence on image and save for viewing