1. Face Recognition with Neural Networks
Jack Breese
Computer Systems
Quarter 2, Pd. 7

2. What is a Neural Network?
Interconnected neurons
Weights
Output

3. Uses of Neural Networks
Pattern Recognition
Face Recognition
OCR

4. Neurons Add up each weighted input
Use an activation function to determine output
Pass on output to next layer

5. Training Neural Networks
Large input set
Outputs are verified, weights adjusted along a gradient based on these results.

6. Program Information Neural Network Library written in C
Currently capable of initializing a two-layer perceptron with working, but unweighted connections.
Can load images up to 500x500 pixels in size.

7. Data Structure typedef struct _connection { float weight;
struct _neuron * from;
} connection;
typedef struct _neuron { //TODO: Implement a neuron which supports connections.
float d;
connection * cons;
}neuron;
neuron* mkneuron(int c) {
neuron* n = malloc(sizeof(neuron));
n->d = 0;
connection * a = malloc(c*sizeof(connection));;
n->cons = a;
return n; }

8. Next Quarter Implement the loading and saving of weight values
Implement training, and then actually train the network