diff --git a/openbr/plugins/nn.cpp b/openbr/plugins/nn.cpp
new file mode 100644
index 0000000..430e3ad
--- /dev/null
+++ b/openbr/plugins/nn.cpp
@@ -0,0 +1,117 @@
+#include <opencv2/ml/ml.hpp>
+
+#include "openbr_internal.h"
+#include "openbr/core/qtutils.h"
+#include "openbr/core/opencvutils.h"
+#include "openbr/core/eigenutils.h"
+#include <QString>
+#include <QTemporaryFile>
+
+using namespace std;
+using namespace cv;
+
+namespace br
+{
+
+static void storeMLP(const CvANN_MLP &mlp, QDataStream &stream)
+{
+    // Create local file
+    QTemporaryFile tempFile;
+    tempFile.open();
+    tempFile.close();
+
+    // Save SVM to local file
+    mlp.save(qPrintable(tempFile.fileName()));
+
+    // Copy local file contents to stream
+    tempFile.open();
+    QByteArray data = tempFile.readAll();
+    tempFile.close();
+    stream << data;
+}
+
+static void loadMLP(CvANN_MLP &mlp, QDataStream &stream)
+{
+    // Copy local file contents from stream
+    QByteArray data;
+    stream >> data;
+
+    // Create local file
+    QTemporaryFile tempFile(QDir::tempPath()+"/MLP");
+    tempFile.open();
+    tempFile.write(data);
+    tempFile.close();
+
+    // Load SVM from local file
+    mlp.load(qPrintable(tempFile.fileName()));
+}
+
+/*!
+ * \ingroup transforms
+ * \brief Wraps OpenCV's multi-layer perceptron framework
+ * \author Scott Klum \cite sklum
+ */
+class MLPTransform : public MetaTransform
+{
+    Q_OBJECT
+
+    Q_PROPERTY(QStringList inputVariables READ get_inputVariables WRITE set_inputVariables RESET reset_inputVariables STORED false)
+    BR_PROPERTY(QStringList, inputVariables, QStringList())
+    Q_PROPERTY(QStringList outputVariables READ get_outputVariables WRITE set_outputVariables RESET reset_outputVariables STORED false)
+    BR_PROPERTY(QStringList, outputVariables, QStringList())
+    Q_PROPERTY(int hiddenLayers READ get_hiddenLayers WRITE set_hiddenLayers RESET reset_hiddenLayers STORED false)
+    BR_PROPERTY(int, hiddenLayers, 1)
+    Q_PROPERTY(QList<int> neuronsPerLayer READ get_neuronsPerLayer WRITE set_neuronsPerLayer RESET reset_neuronsPerLayer STORED false)
+    BR_PROPERTY(QList<int>, neuronsPerLayer, QList<int>() << 6)
+
+    CvANN_MLP mlp;
+
+    void init()
+    {
+        Mat layers = Mat(hiddenLayers, 1, CV_32SC1);
+        for (int i=0; i<hiddenLayers; i++) {
+            layers.row(i) = Scalar(neuronsPerLayer.at(i));
+        }
+        mlp.create(layers,CvANN_MLP::SIGMOID_SYM, 1, 1);
+    }
+
+    void train(const TemplateList &data)
+    {
+        Mat _data = OpenCVUtils::toMat(data.data());
+
+        // Assuming data has n templates
+        // _data needs to be n x size of input layer
+        // Labels needs to be a n x outputs matrix
+        // For the time being we're going to assume a single output
+        Mat labels = Mat::zeros(data.size(),inputVariables.size(),CV_32F);
+        for (int i=0; i<inputVariables.size(); i++)
+            labels.col(i) += OpenCVUtils::toMat(File::get<float>(data, inputVariables.at(i)));
+
+        mlp.train(_data,labels,Mat());
+    }
+
+    void project(const Template &src, Template &dst) const
+    {
+        // See above for response dimensionality
+        Mat response(outputVariables.size(), 1, CV_32FC1);
+        mlp.predict(src.m().reshape(1,1),response);
+
+        for (int i=0; i<outputVariables.size(); i++) dst.file.set(outputVariables.at(i),response.at<float>(i,0));
+    }
+
+    void load(QDataStream &stream)
+    {
+        loadMLP(mlp,stream);
+    }
+
+    void store(QDataStream &stream) const
+    {
+        storeMLP(mlp,stream);
+    }
+};
+
+BR_REGISTER(Transform, MLPTransform)
+
+} // namespace br
+
+#include "nn.moc"