The Artificial Neuron
History
Comparison
Architecture
Applications
Future
Sources
Neural Network Header

Other Applications of Neural Networks
Here are a few of the more quirky applications of Neural Networks:

<<to top>>

image courtesy Notre Dame
Bill's Notre Dame Football Predictor
  1. Train the network on historical data for offensive plays given particular game situations
  2. Use network to predict what offensive play will be chosen at any point in the game
http://robby.caltech.edu/~goodwine/football.html

<<to top>>
Getting rat thoughts to move robotic parts

1. Train a rat to press a lever, which activates a robotic arm.  Robotic arm delivers reward to rat.

2. Attach a 16-probe array to the rat's brain that can record the activity of 30 neurons at once.

3. Train a neural network program to recognize brain-activity patterns during a lever press.

4. Neural network can predict movement from the rat's brain activity alone, so when the rat's brain activity indicates that it is about to press the lever, robotic arm moves and rewards the rat - the rat does not need to press the lever, but merely needs to "think" about doing so (whatever rat "thinking" may  beÉ)

http://www.sciam.com/1999/1199issue/1199techbus2.html


<<to top>>
ALVINN, the self-driving car


(this car is not ALVINN, it's from PhotoEssentials)

http://www.cs.cmu.edu/afs/cs.cmu.edu/project/alv/member/www/projects/ALVINN.html

1. Train single hidden layer back-propagation network on images of the road under a variety of conditions and the appropriate steering modification for each condition.

2. Allow car to drive itself: a video image from the onboard camera is injected into the input layer. Activation is passed forward through the network and a steering command is read off the output layer. The most active output unit determines the direction in which to steer.

3. Allow car to drive itself at speeds up to 70 mph on Pittsburgh freeways

<<to top>>
 

An Analysis of Sheep Rumination and Mastication
Anthony Zaknich and Sue K Baker (1998), "A real-time system for the characterisation of sheep feeding phases from acoustic signals of jaw sounds," Australian Journal of Intelligent Information Processing Systems (AJIIPS), Vol. 5, No. 2,Winter 1998.

1. Attach radio microphones to the top of sheep heads to transmit chewing sounds

2. Record chewing sounds and times of chewing

3. Use a neural network classifier, using your time and frequency data as input, to predict future rumination and mastication time periods

Why??? we haven't a clue!  The online abstract didn't tell us.


<<to top>>

Back to Applications