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Selected Applications of MLP

Christopher Bishop, Pattern Recognition and MachineLearning, Springer, 2006 – Chapter 5

5-Aug-13 http://w3.ualg.pt/~jvo/ml

Machine VisionRobust Pattern DetectionSignal FilteringVirtual RealityData SegmentationData Compression

Data MiningText MiningArtificial LifeAdaptive Control, Optimisation, and Scheduling…

Some application areas

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Selected applicationsBackpropagation has been used for a large number of practical applications.

Recognizing hand-written charactersStock market prediction Fraud detection in credit cardSpeech recognition Predicting the next word in a sentence (from the previous words)Face recognitionSignature recognitionMine-rock detector

ALVINN (Pomerleau, 1989)Autonomous vehicle controlled by an artificial neural networkDrives faster than 80km/h in public highways

From: http://www.ri.cmu.edu/projects/project_160.html

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Mine-rock detector (Churland, 1988)

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Mine-Rock Detector

5-Aug-13 http://w3.ualg.pt/~jvo/ml

NETtalk (Sejnowski & Rosenberg, 1987)Learn to pronounce English text from examples.

Training data are 1000 most occuring words and their phonemes.

Input: 7 consecutive characters from written text presented in a moving window that scans text.

Output: phoneme code giving the pronunciation of the letter at the center of the input window.

Network topology: 7x29 inputs, 80 hidden units and 26 output units. Sigmoid units in hidden and output layer.

nettalk.mp3

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Adaptive control

R. Pfeifer and C. Scheier , Understanding Intelligence, MIT Press, 1999

5-Aug-13 http://w3.ualg.pt/~jvo/ml

Aplicações: controlo adaptativo

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OCRTypically performed by a MLP trained with Backpropagation

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Signature recognition

http://www.advancedsourcecode.com

5-Aug-13 http://w3.ualg.pt/~jvo/ml

Kohonen maps

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5-Aug-13 http://w3.ualg.pt/~jvo/ml

In the human cortex, multi-dimensional sensory input spaces (e.g., visual input, tactile input) are represented by two-dimensional maps.

The projection from sensory inputs onto such maps is topology conserving, meaning that neighboring areas in these maps represent neighboring areas in the sensory input space.

Topologic maps in the brain

5-Aug-13 http://w3.ualg.pt/~jvo/ml

Topologic maps in the brainExamples of topologic conserving mapping between input and output spaces:

Retintopoical mapping between the retina and the cortexOcular dominanceSomatosensory mapping (the homunculus)

For example, arm and hand are represented by neighboring areas in the sensory cortex.

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Cortical homunculus

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Models of sensory and motor homunculi at the Natural History Museum in London