10-19-2024, 04:42 PM
(translated by Google translator)
Hello, friends.
My entertainment with the creation of SB-Neurons and SB-Neural Networks gave me another pleasure.
I learned that the methods that other people use to train classical neurons to recognize a straight line on a matrix of pixels are more complicated than my method.
I think this is because I will be using SB-Neurons, not classical neurons.
As you know, SB-Neurons have an advantage because they use the principle of changing the activation function, instead of the principle of changing the weights on the neuron's inputs.
Now that I understand everything I need to create a SB-Neural Network, I have the opportunity to write the SB code of a new demo program.
This program will demonstrate how my SB-Neural Network will recognize a "cross" on a matrix of 9 by 9 pixels.
The "cross" can have any size, rotation angle, and position on the matrix.
The neural network will not look for the "cross" itself, but for a set of "features" that characterize any normal "cross".
This is the "end of the line" feature;
the "presence of two pairs of "ends of the line" of opposite directions on the matrix" feature;
the "intersection of two lines" feature;
and the "straight line" feature.
If all of the listed "features" are detected, my SB-Neural Network will say that a "cross" is depicted on the matrix.
This is the kind of entertainment I have at the moment.
(It's a shame that no one else talks about their interesting SB-projects
)
Hello, friends.
My entertainment with the creation of SB-Neurons and SB-Neural Networks gave me another pleasure.
I learned that the methods that other people use to train classical neurons to recognize a straight line on a matrix of pixels are more complicated than my method.
I think this is because I will be using SB-Neurons, not classical neurons.
As you know, SB-Neurons have an advantage because they use the principle of changing the activation function, instead of the principle of changing the weights on the neuron's inputs.
Now that I understand everything I need to create a SB-Neural Network, I have the opportunity to write the SB code of a new demo program.
This program will demonstrate how my SB-Neural Network will recognize a "cross" on a matrix of 9 by 9 pixels.
The "cross" can have any size, rotation angle, and position on the matrix.
The neural network will not look for the "cross" itself, but for a set of "features" that characterize any normal "cross".
This is the "end of the line" feature;
the "presence of two pairs of "ends of the line" of opposite directions on the matrix" feature;
the "intersection of two lines" feature;
and the "straight line" feature.
If all of the listed "features" are detected, my SB-Neural Network will say that a "cross" is depicted on the matrix.
This is the kind of entertainment I have at the moment.
(It's a shame that no one else talks about their interesting SB-projects
)