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Generating Dispatching Rules for the Interrupting Swap-Allowed Blocking Job Shop Problem Using Graph Neural Network and Reinforcement Learning
The interrupting swap-allowed blocking job shop problem (ISBJSSP) is a complex scheduling problem that is able to model many manufacturing planning and logistics applications realistically by addressing both the lack of storage capacity and unforeseen production interruptions.
Automatic Volumetric Segmentation of Additive Manufacturing Defects with 3D U-Net
Segmentation of additive manufacturing (AM) defects in X-ray Computed Tomography (XCT) images is challenging, due to the poor contrast, small sizes and variation in appearance of defects.
Building Information Modeling and Classification by Visual Learning At A City Scale
In the first case, a machine learning-assisted framework, BRAILS, is proposed for city-scale building information modeling.
Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning
Transfer learning is leveraged to reduce the training data demands and increase the prediction accuracy of the trained model.
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