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Keywords: k-means clustering
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Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A070, August 14–17, 2022
Paper No: DETC2022-88313
... identifies anomalous melt pools by identifying images with a large reconstruction loss. The K-Means clustering or autoencoder provides labels that can be used for training a convolutional neural network image classifier. The image classifier can then be used to identify anomalous melt pools during the LPBF...
Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 6: 34th International Conference on Design Theory and Methodology (DTM), V006T06A044, August 14–17, 2022
Paper No: DETC2022-89746
... and patent citation count. Finally, by combining the TRIZ clustering and the trained autoencoder, we show that high reconstruction error patents may be harder to assign to TRIZ methods than low reconstruction error patents. TRIZ unsupervised machine learning K-means clustering Gaussian mixture model...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 4: 22nd International Conference on Advanced Vehicle Technologies (AVT), V004T04A007, August 17–19, 2020
Paper No: DETC2020-22339
...Abstract Abstract This paper presents a clustering technique for the detection of the obstacles and lane boundaries on a road. The algorithm consists of two nested clustering stages. The first stage is based on hierarchical clustering, and the second on k-means clustering. The method exploits...