27 citations · 46 across the 4 of their papers we have counts for
4 papers
Domain-knowledge Inspired Pseudo Supervision (DIPS) for Unsupervised Image-to-Image Translation Models to Support Cross-Domain Classification
Firas Al-Hindawi, Md Mahfuzur Rahman Siddiquee, Teresa Wu +2
The ability to classify images is dependent on having access to large labeled datasets and testing on data from the same domain that the model can train on. Classification becomes…
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu +5
Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare disease…
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation
Firas Al-Hindawi, Tejaswi Soori, Han Hu +4
The detection of critical heat flux (CHF) is crucial in heat boiling applications as failure to do so can cause rapid temperature ramp leading to device failures. Many machine lear…
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu +3
Automated anomaly detection from medical images, such as MRIs and X-rays, can significantly reduce human effort in disease diagnosis. Owing to the complexity of modeling anomalies…