Transcript Dynamic Hand Written Character Recognition

Dynamic Hand Written Character
Recognition
Shi-Ting Zhou
Project Goal
• Devise a new approach in recognizing hand
written characters without training process in
respective classical neural network
approaches.
• Validate the proposed technique by testing on
hand written digits
Motivation
• Classical ANN does not possess the merits of
biological neural systems
• Real biological neural systems are dynamical
• Classical ANN approaches ignore 2-D
information of inputs
Methodology
• Devise a simulator capable of simulating the
dynamics of elastic body in attracting force
field
• Build templates of written digits
• Test on the MNIST DATABASE of handwritten
digits (“http://yann.lecun.com/exdb/mnist/”)
Neural Network?
• Can be implemented in the form of recurrent
neural network.
Discussion
• Potential usage on other type of recognition
task
• Can have a 3-D version. 1-D lines become 2-D
manifolds
• Problem: Computationally intensive if have a
lot of templates
• Solution: Targeting at smaller and repeating
features instead of entire symbol