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Learning using privileged information for segmenting tumors on digital mammograms
We repeat the student training procedure by providing the assistance of the teacher model this time.
A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation
Recent studies indicate that deep learning plays a crucial role in the automated visual inspection of road infrastructures.
Transferability limitations for Covid 3D Localization Using SARS-CoV-2 segmentation models in 4D CT images
In this paper, we investigate the transferability limitations when using deep learning models, for semantic segmentation of pneumonia-infected areas in CT images.
Evaluating Transferability for Covid 3D Localization Using CT SARS-CoV-2 segmentation models
Recent studies indicate that detecting radiographic patterns on CT scans can yield high sensitivity and specificity for Covid-19 localization.
Space-Time Domain Tensor Neural Networks: An Application on Human Pose Classification
Recent advances in sensing technologies require the design and development of pattern recognition models capable of processing spatiotemporal data efficiently.
