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Found 3 papers, 1 papers with code
FeaInfNet: Diagnosis in Medical Image with Feature-Driven Inference and Visual Explanations
Due to the unique multi-instance learning of medical images and the difficulty in identifying decision-making regions, many interpretability models that have been proposed still have problems of insufficient accuracy and interpretability in medical image disease diagnosis.
Hybrid Interference Mitigation Using Analog Prewhitening
This paper proposes a novel scheme for mitigating strong interferences, which is applicable to various wireless scenarios, including full-duplex wireless communications and uncoordinated heterogenous networks.
Learning Smooth Representation for Unsupervised Domain Adaptation
When constructing a deep end-to-end model, to ensure the effectiveness and stability of unsupervised domain adaptation, three critical factors are considered in our proposed optimization strategy, i. e., the sample amount of a target domain, dimension and batchsize of samples.
Ranked #1 on
Domain Adaptation
on SVNH-to-MNIST
