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Found 3 papers, 1 papers with code
Deep Transformers Thirst for Comprehensive-Frequency Data
We study an NLP model called LSRA, which introduces IB with a pyramid-free structure.
U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation
This paper proposes a novel U-Net variant using stacked dilated convolutions for medical image segmentation (SDU-Net).
Weakly Supervised Context Encoder using DICOM metadata in Ultrasound Imaging
Modern deep learning algorithms geared towards clinical adaption rely on a significant amount of high fidelity labeled data.
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