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tvhahn
ml-tool-wear tvhahn
24
63
mit
3
Anomaly detection on the UC Berkeley milling data set using a disentangled-variational-autoencoder (beta-VAE). Replication of results as described in article "Self-Supervised Learning for Tool Wear Mo...
trend recall milling beta-vae precision masc-thesis deep-learning latent-spaces anomaly-detection tool-wear-monitoring advanced-manufacturing tool-condition-monitoring machinery-condition-monitoring
Created 2020-08-21
66 commits to master branch, last one 3 years ago