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When Medical Imaging Met Self-Attention: A Love Story That Didn't Quite Work Out
To evaluate this trend for medical imaging, we extend two widely adopted convolutional architectures with different self-attention variants on two different medical datasets.
Reducing Bias in Pre-trained Models by Tuning while Penalizing Change
If later such a bias is discovered during inference or deployment, it is often necessary to acquire new data and retrain the model.
The Power of Properties: Uncovering the Influential Factors in Emotion Classification
We introduce a workflow to evaluate explicit properties and their impact.
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