Aluminum Casting Inspection Using Deep Learning: A Method Based on Convolutional Neural Networks

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Detection of a casting defect tracked by deep convolution neural network

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Defect Detection of Aluminum Alloy Wheels in Radiography Images Using Adaptive Threshold and Morphological Reconstruction

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Deep learning

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A sparse-representation-based robust inspection system for hidden defects classification in casting components

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Representation Learning: A Review and New Perspectives

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Detection of flaws in aluminium castings: a comparative study between generative and discriminant approaches

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Defect detection of castings in radiography images using a robust statistical feature

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Statistical detection of defects in radiographic images using an adaptive parametric model

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Flaw detection in aluminium die castings using simultaneous combination of multiple views

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Visual inspection of glass bottlenecks by multiple-view analysis

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Automatic multiple view inspection using geometrical tracking and feature analysis in aluminum wheels

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The Pascal Visual Object Classes (VOC) Challenge

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Application of a new image segmentation method to detection of defects in castings

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X-ray based methods for non-destructive testing and material characterization

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