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Found 7 papers, 0 papers with code
CMISR: Circular Medical Image Super-Resolution
Five CMISR algorithms are respectively proposed based on the state-of-the-art open-loop MISR algorithms.
CSwin2SR: Circular Swin2SR for Compressed Image Super-Resolution
Closed-loop negative feedback mechanism is extensively utilized in automatic control systems and brings about extraordinary dynamic and static performance.
ICRICS: Iterative Compensation Recovery for Image Compressive Sensing
The proposed method depends on any existing approaches and upgrades their reconstruction performance by adding negative feedback structure.
Patch Selection for Melanoma Classification
We find that, in addition to requiring less preprocessing time, the classifiers trained on the datasets of patches selected based on entropy converge faster than on those selected based on the spectral similarity criterion and, furthermore, lead to higher accuracy.
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications
Last years have been characterized by an upsurge of opaque automatic decision support systems, such as Deep Neural Networks (DNNs).
BIG-bench Machine Learning
Explainable artificial intelligence
+2
Cascade Decoders-Based Autoencoders for Image Reconstruction
It is evaluated by the experimental results that the proposed autoencoders outperform the classical autoencoders in the performance of image reconstruction.
Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts
We bring light by providing an expert-aligned feature relevance score highlighting the disagreement between a credit risk expert and a model feature attribution explanation in order to better quantify the convergence towards a better human-aligned decision making.
