# Applying Machine Learning to 2D Laser Scanner Data

We are using 2D Laser Scanner to scan various objects of different geometric shapes for e.g. cylinder, spiked, cylinder with notch, cylinder with curved edges e.t.c. The dataset contains points in the format [x, y] with the dimension of 1 complete scan being 160x2. The goal is to use these scan points to classify the various shapes.

I have used a multilayer NN with sigmoid as the final layer and Adadelta optimizer for this problem but the accuracy reaches only upto 70%.

Can anyone recommend a proper model that can be used for Laser Scanner Data Classification?

## MODEL

def baseline_model():
model = Sequential()