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Found 6 papers, 0 papers with code
Defending Person Detection Against Adversarial Patch Attack by using Universal Defensive Frame
Person detection has attracted great attention in the computer vision area and is an imperative element in human-centric computer vision.
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation
Experimental results show that the proposed method could provide useful uncertainty information by Bayesian approximation with the efficient ensemble model generation and improve the predictive performance.
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack
After the ensemble models are trained, it can hide the gradient efficiently and avoid the gradient-based attack by the random layer sampling method.
Revisiting Role of Autoencoders in Adversarial Settings
Through the comprehensive experimental results and analysis, this paper presents the inherent property of adversarial robustness in the autoencoders.
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation
In order to learn deep network model to be well-behaved in bio-image computing fields, a lot of labeled data is required.
ICADx: Interpretable computer aided diagnosis of breast masses
In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework.
