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Found 5 papers, 1 papers with code
Improving Object Detector Training on Synthetic Data by Starting With a Strong Baseline Methodology
Besides reaching relatively strong performance without any specialized synthetic data transfer methods, we show that our methods improve the state of the art on synthetic data trained object detection for the RarePlanes and DGTA-VisDrone datasets, and reach near-perfect performance on an in-house vehicle detection dataset.
Deep Learning for Detection and Localization of B-Lines in Lung Ultrasound
B-line artifacts in LUS videos are key findings associated with pulmonary congestion.
Corneal Pachymetry by AS-OCT after Descemet's Membrane Endothelial Keratoplasty
In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans.
Quantifying Graft Detachment after Descemet's Membrane Endothelial Keratoplasty with Deep Convolutional Neural Networks
A second DMEK expert annotated the test set to determine inter-rater performance.
Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study
We investigated three methods to achieve high classification performance, measured by the area under the receiver operating curve (ROC-AUC).
