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Found 3 papers, 2 papers with code
ADFA: Attention-augmented Differentiable top-k Feature Adaptation for Unsupervised Medical Anomaly Detection
We then apply differentiable top-k feature adaptation to train the patch descriptor, mapping the extracted feature representations to a new vector space, enabling effective detection of anomalies.
Elucidating Meta-Structures of Noisy Labels in Semantic Segmentation by Deep Neural Networks
Our understanding of the learning behavior of DNNs trained by noisy segmentation labels remains limited.
Deep Neural Networks Learn Meta-Structures from Noisy Labels in Semantic Segmentation
When trained with these noisy labels, DNNs provide largely the same segmentation performance as trained by the original ground truth.
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