no code implementations • 20 Apr 2024 • Junpu Wang, Guili Xu, Chunlei Li, Guangshuai Gao, Yuehua Cheng
Unsupervised anomaly detection using only normal samples is of great significance for quality inspection in industrial manufacturing.
no code implementations • 17 Jul 2022 • Junpu Wang, Guili Xu, Fuju Yan, Jinjin Wang, Zhengsheng Wang
Then, the patch aggregation blocks are used to generate multi-scale representation with four hierarchies, each of them is followed by a series of DefT blocks, which respectively include a locally position-aware block for local position encoding, a lightweight multi-pooling self-attention to model multi-scale global contextual relationships with good computational efficiency, and a convolutional feed-forward network for feature transformation and further location information learning.
7 code implementations • 8 Oct 2019 • Daliang Li, Junpu Wang
With 10 distinct participants, the final test accuracy of each model on average receives a 20% gain on top of what's possible without collaboration and is only a few percent lower than the performance each model would have obtained if all private datasets were pooled and made directly available for all participants.