no code implementations • 15 Jun 2023 • Grant Sinha, Krish Parmar, Hilda Azimi, Amy Tai, Yuhao Chen, Alexander Wong, Pengcheng Xi
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).
1 code implementation • 14 Sep 2022 • Hilda Azimi, Steven Chang, Jonathan Gold, Koray Karabina
A wide range of applications from signature verification to electronic document processing can be realized by implementing efficient and accurate handwriting recognition algorithms.
no code implementations • 18 May 2022 • Hilda Azimi, Ashkan Ebadi, Jessy Song, Pengcheng Xi, Alexander Wong
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.
no code implementations • 22 Feb 2022 • Hilda Azimi, Jianxing Zhang, Pengcheng Xi, Hala Asad, Ashkan Ebadi, Stephane Tremblay, Alexander Wong
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.
no code implementations • 4 May 2021 • Jianxing Zhang, Pengcheng Xi, Ashkan Ebadi, Hilda Azimi, Stephane Tremblay, Alexander Wong
The COVID-19 pandemic has had devastating effects on the well-being of the global population.