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Found 6 papers, 4 papers with code
Multi-Scale Feature Fusion using Parallel-Attention Block for COVID-19 Chest X-ray Diagnosis
Under the global COVID-19 crisis, accurate diagnosis of COVID-19 from Chest X-ray (CXR) images is critical.
Augmenting endometriosis analysis from ultrasound data with deep learning
Our objective in this work is to investigate the potential of deep learning methods to classify endometriosis from ultrasound data.
Multi-Feature Vision Transformer via Self-Supervised Representation Learning for Improvement of COVID-19 Diagnosis
To improve the diagnostic performance of CXR imaging a growing number of studies have investigated whether supervised deep learning methods can provide additional support.
Multi-Feature Semi-Supervised Learning for COVID-19 Diagnosis from Chest X-ray Images
The requirement for a large amount of labeled data is one of the major problems of deep learning methods when deployed in the medical domain.
Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network
The enhanced images, together with the original CXR data, are used as an input to our proposed CNN architecture.
Shape-from-Mask: A Deep Learning Based Human Body Shape Reconstruction from Binary Mask Images
In this paper, we propose a deep learning based reconstruction of 3D human body shape from 2D orthographic views.
