diff --git a/dlib/cmake b/dlib/cmake
index 33c2edfc3..e13d04cca 100644
--- a/dlib/cmake
+++ b/dlib/cmake
@@ -78,6 +78,12 @@ elseif (MSVC OR "${CMAKE_CXX_COMPILER_ID}" STREQUAL "MSVC") # else if using Visu
         message(STATUS "Enabling SSE2 instructions")
         add_definitions(-DDLIB_HAVE_SSE2)
     endif()
+
+   # By default Visual Studio does not support .obj files with more than 65k sections
+   # Code generated by file_to_code_ex and code using DNN module can have them
+   # this flag enables > 65k sections, but produces .obj files that will not be readable by
+   # VS 2005
+   set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /bigobj")
 endif()
 
 
diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
index 5b6cf40a1..153fe6b0e 100644
--- a/examples/CMakeLists.txt
+++ b/examples/CMakeLists.txt
@@ -10,10 +10,6 @@ PROJECT(examples)
 
 include(../dlib/cmake)
 
-if (POLICY CMP0054)
-    cmake_policy(SET CMP0054 NEW)
-endif()
-
 # Tell CMake to compile a program.  We do this with the ADD_EXECUTABLE()
 # statement which takes the name of the output executable and then a list of
 # .cpp files to compile.  Here each example consists of only one .cpp file but
@@ -35,13 +31,6 @@ ENDMACRO()
 
 # The deep learning toolkit requires a C++11 capable compiler.  
 if (COMPILER_CAN_DO_CPP_11)
-   # Visual Studio Specific
-   # DNN module produces long type names for NN definitions - disable this warning for MSVC
-   # And when compiling Debug mode file will be too big for normal compilation
-   if (MSVC OR "${CMAKE_CXX_COMPILER_ID}" STREQUAL "MSVC") 
-      message(STATUS "Enabling Visual Studio specific flags for DNN")
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4503 /bigobj")
-   endif()
    add_example(dnn_mnist_ex)
    add_example(dnn_mnist_advanced_ex)
    add_example(dnn_inception_ex)
diff --git a/examples/dnn_inception_ex.cpp b/examples/dnn_inception_ex.cpp
index f3f2bfd14..0fa92e4f0 100644
--- a/examples/dnn_inception_ex.cpp
+++ b/examples/dnn_inception_ex.cpp
@@ -23,10 +23,17 @@
     the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
 */
 
+// DNN module uses template-based network declaration that leads to very long
+// type names. Visual Studio will produce Warning C4503 in such cases
+#ifdef _MSC_VER
+#   pragma warning( disable: 4503 )
+#endif
 #include <dlib/dnn.h>
+
 #include <iostream>
 #include <dlib/data_io.h>
 
+
 using namespace std;
 using namespace dlib;
 
@@ -84,7 +91,7 @@ int main(int argc, char** argv) try
     // Make an instance of our inception network.
     net_type net;
     cout << "The net has " << net.num_layers << " layers in it." << endl;
-    cout << net << endl;
+//    cout << net << endl;
 
 
     cout << "Traning NN..." << endl;
diff --git a/examples/dnn_mnist_advanced_ex.cpp b/examples/dnn_mnist_advanced_ex.cpp
index 4da911b4f..ab9527a25 100644
--- a/examples/dnn_mnist_advanced_ex.cpp
+++ b/examples/dnn_mnist_advanced_ex.cpp
@@ -10,6 +10,11 @@
         - Accessing and configuring layers in a network
 */
 
+// DNN module uses template-based network declaration that leads to very long
+// type names. Visual Studio will produce Warning C4503 in such cases
+#ifdef _MSC_VER
+#   pragma warning( disable: 4503 )
+#endif
 
 #include <dlib/dnn.h>
 #include <iostream>