per-class

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jesiekjakub / rnn-defect-detection

Multi-label time-series defect detection using Bi-directional LSTM with per-class attention and Seq2Seq autoencoder. Identifies manufacturing defects across 3 sensors with temporal localization and root cause analysis.

pytorch rnn autoencoder seq2seq attention rnn-pytorch attention-seq2seq per-class

Updated Feb 13, 2026
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per-class

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jesiekjakub / rnn-defect-detection

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