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Found 5 papers, 2 papers with code
Ensembling and Test Augmentation for Covid-19 Detection and Covid-19 Domain Adaptation from 3D CT-Scans
Since the emergence of Covid-19 in late 2019, medical image analysis using artificial intelligence (AI) has emerged as a crucial research area, particularly with the utility of CT-scan imaging for disease diagnosis.
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models
Our experimental study conducted on a lymphoma dataset of 157 patients shows the promising performance of our mono-modal classification model, outperforming six recent state-of-the-art methods.
SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix Data Augmentation
These grid-based methods produce a new style of image transformations using the dropping and fusing of information.
MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19
However, at the moment, there are no available large dataset of masked face images that permits to check if detected masked faces are correctly worn or not.
Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19
Tailored deep learning models are proposed to detect pneumonia infection cases, notably viral cases.
