multi layer perceptron & back propagation
TRANSCRIPT
Content
• Why Neural Net came back?
• Single Layer Perceptron
• Multi Layer Perceptron
• Traffic Sign Lane Guessing
Why Neural Net Came back?
Stallkamp, Johannes, et al. "Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition." Neural networks 32 (2012): 323-332.
Face net: 99.6% Deep Face : 97.25%
Single Layer PerceptronFeed Forward
Activation Functionsstep function sign function identity function
sigmoid function hyper tangent function
Limitation of Single Layer Perceptron
But Single Layer Perceptron cannot classify XOR Problem
Multi Layer Perceptron
Multi Layer Perceptron
Hidden Layer
Output Layer
Input Layer
Ex)
✕✕
Feed Forward
How to Learn Perceptron?Error Function
Error Function
Target Value
Output Value
How to Learn Perceptron?Delta Learning Rule
E
(weight)
How to Learn Perceptron?Delta Learning Rule
new weightcurrent weightlearning rateError Function
How to Learn Perceptron?Delta Learning Rule
E
(weight)
new weightcurrent weightlearning rateError Function
Back Propagation
Hidden Layer
Output Layer
Input Layer
new weight
current weight
learning rate
Error Function
Target Value
Output Value
Back Propagation
Hidden Layer
Output Layer
Input Layer
new weight
current weight
learning rate
Error Function
Good for Design in Parallels Architecture