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TU DelftA Machine Learning Approachto Fringe-Location IdentificationFiras Sawaf and Roger Groves ● FASIG - Photon 12 ● Durham ● September 2012
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Fringe LocationEdge detection
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Fringe LocationPre-filtering
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A Machine Learning ApproachFree online course
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A Machine Learning ApproachNeural networks
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A Machine Learning ApproachTraining
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A Machine Learning ApproachTesting, training set 99.9%
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A Machine Learning ApproachTesting, over-fitting
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A Machine Learning ApproachTesting, cross-validation set 89.9%
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A Machine Learning ApproachTesting, cross-validation set
MCC% = Threshold% * MCC
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A Machine Learning ApproachIntuition
• AA: Ability to Absorb
• AG: Ability to Generalise
• AIM: Absorption vs. Ideal Measure
• SAG: Spread of Absorption vs. Generalisation
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A Machine Learning ApproachPerformance - Large AIM, Small SAG
120,000 training examples, 200 nodes in hidden layer
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A Machine Learning ApproachPerformance - Medium AIM, Large SAG
30,000 training examples, 800 nodes in hidden layer
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A Machine Learning ApproachPerformance - Small AIM, Large SAG
30,000 training examples, 1600 nodes in hidden layer
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A Machine Learning ApproachPerformance - Medium AIM, Medium SAG
120,000 training examples, 1600 nodes in hidden layer
