Image Classification. MSc Image Processing Assignment March 2003. Summary. Introduction Classification using neural networks Perceptron Multilayer perceptron Applications. Introduction. Definition Assignment of a physical object to one of several prespecified categories Unsupervised
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Image Classification
MSc Image Processing Assignment
March 2003
For more details
See Image Processing course
Supervised
Unsupervised
kmeans
Fuzzy kmean
Pattern recognition
Algebraic
Parametric
Nonparametric
Neural nets
SVM
Bayes
Minimum distance
Knearest neighbour
Decision trees
Classification
Classification
x1
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w1
f
y=f(wi xi + w0)
wn
xn
x=(x1…xn) input vector
w=(w0…wn) weight vector
f activation function
1
1
w1x1+w2x2+w0=0
x1
1 1
x2
1
w0=1
1 1
1 1
1
1
x1
w1=1
w1=1
sign
w2=1
x2
x2
+
1+x1+x2=0
x1

Problem when
Data nonlinearly separable
For more details
Matlab classification toolbox http://tiger.technion.ac.il/~eladyt/Classification_toolbox.html
outputs
inputs
y
w0
w1
w2
x1
x2
Output layer
Input layer
1st hidden layer
2nd hidden layer
F
E
A
T
U
R
E
S
O
U
T
P
U
T
8 features
10 neurons
10 neurons
10 neurons
10 neurons
For more details
See our program
To go further
See Neural Network Toolbox, demo on generalisation