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Found 5 papers, 1 papers with code
Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions
To address these issues, two models are trained and compared, one based on convolutional neural networks and the other on Bidirectional Encoder representation for Image Transformers (BEiT).
Improving Accuracy and Explainability of Online Handwriting Recognition
A wide range of applications from signature verification to electronic document processing can be realized by implementing efficient and accurate handwriting recognition algorithms.
COVID-Net UV: An End-to-End Spatio-Temporal Deep Neural Network Architecture for Automated Diagnosis of COVID-19 Infection from Ultrasound Videos
Besides vaccination, as an effective way to mitigate the further spread of COVID-19, fast and accurate screening of individuals to test for the disease is yet necessary to ensure public health safety.
Improving Classification Model Performance on Chest X-Rays through Lung Segmentation
Our approach is designed in a cascaded manner and incorporates two modules: a deep neural network with criss-cross attention modules (XLSor) for localizing lung region in CXR images and a CXR classification model with a backbone of a self-supervised momentum contrast (MoCo) model pre-trained on large-scale CXR data sets.
COVID-19 Detection from Chest X-ray Images using Imprinted Weights Approach
The COVID-19 pandemic has had devastating effects on the well-being of the global population.
