CS-660 Interactive Machine Learning Final Paper.

Finally finished my semester project to ID stairs using Convolutional Neural Nets (CNN) for SEAR-RL.

Read it here if you want.

The Effect of Data Content and Human Oracles on Convolutional Neural Networks and Incremental Learning

If you just want to tl;dr here it is (nothing ground breaking):

1. If you want to ID 3D objects with a CNN, you are better off using 3D data (point clouds) then 2D image data (even for 2D CNNs like I used).
2. Using human reinforcement in incremental training of Neural Nets does not really improve training.  It might help if you are adding new classes to ID along with the data, but that would be future work to explore.

You can check out the code for the project here:

https://github.com/ForeverTangent/CS-660-Semester-Project-V2

Although you need to get the data I collected for training from here:

https://drive.google.com/open?id=1bwJsnJfwcYEMXWGummS_NNne8PGf9P3r

(the data is too big to store on GitHub)

To run everything you need.

• Anaconda 5.0 / Python 3.6
• TensorFlow 1.1.0
• Keras 2.0.8

And if you want to check out the data collection Application for iOS (of just need a start Occipital Structure App written for Swift 4.0) you can get that here:

https://github.com/ForeverTangent/SEAR-DC