Neural network feature extraction for the tasks of visual recognition

Abstract EN

In this Paper, a neural network image recognition system is used.

The Neocognitron[8] in that system is used as feature extractor, then the feature are classified by using a multilayered feedforward network to generate recognition codes.

Many neural learning algorithms are used to extract the feature, then comparison among them is presented.

Finally a comparison between most active algorithms among them with respect to the whole performance of the of the designed system is presented.

The biases used in MBCL (Modified Bias Competitive Learning) played an important role to improve the performance of competitive learning algorithms.

Using SOFM (Self Organizing Feature Map) to extract features gave better recognition rate than MBCL and other algorithms.