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Found 3 papers, 1 papers with code
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains
In this work, we present an idea to remove non-causal factors from common features by multi-view adversarial training on source domains, because we observe that such insignificant non-causal factors may still be significant in other latent spaces (views) due to the multi-mode structure of data.
Layer-wise Customized Weak Segmentation Block and AIoU Loss for Accurate Object Detection
The anchor-based detectors handle the problem of scale variation by building the feature pyramid and directly setting different scales of anchors on each cell in different layers.
Deep Double-Side Learning Ensemble Model for Few-Shot Parkinson Speech Recognition
To solve these two problems, based on the existing Parkinson speech feature data set, a deep double-side learning ensemble model is designed in this paper that can reconstruct speech features and samples deeply and simultaneously.
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