About Emergent X
This app allows the user to interactively experiment with and visualize the training of a single neuron (feature detector) in an unsupervised neural network. The user provides the online "training data" via taking photos....
This app allows the user to interactively experiment with and visualize the training of a single neuron (feature detector) in an unsupervised neural network. The user provides the online "training data" via taking photos.
Instructions: take photos and be patient -- even small neural networks are computationally intensive!
The network converges on the first "principal component" or most often occurring 2 x 2 feature pattern that multiple images share in common.
This network implements only local learning rules:
1. A neuron is competitive: if it frequently does not fire, it decreases its threshold to respond to stimuli with greater variance.
2. A neuron is thrifty: if it frequently fires, it increases its threshold
3. When a neuron fires, it tunes its "weights" to move in a direction which will increase the likelihood of a similar pattern triggering it in the future.
Example: if a post synaptic neuron was responding to a high amplitude signal, but now responds to a lower amplitude signal (due to threshold decrease), its weights will move towards the lower amplitude signal.
Network structure:
1. Input layer: 8 x 8 x 3 (3 color channels)
2. Convolutional layer: 2 x 2 x 3 ( 1 neuron with 12 synapses)
3. Activation Map: 7 x 7 x 1
Note: Color channels are preprocessed to respond similarly regardless of lighting.
Previous Versions
Here you can find the changelog of Emergent X since it was posted on our website on 2016-10-01 04:58:48.
The latest version is 1.0 and it was updated on 2024-04-22 10:57:26. See below the changes in each version.
Emergent X version 1.0
Updated At: 2016-08-06
Disclaimer
Official Google Play Link
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