June 30, 2022, 1:12 a.m. | Ricardo Bigolin Lanfredi, Mingyuan Zhang, William F. Auffermann, Jessica Chan, Phuong-Anh T. Duong, Vivek Srikumar, Trafton Drew, Joyce D. Schroeder,

cs.CV updates on arXiv.org arxiv.org

Deep learning has shown recent success in classifying anomalies in chest
x-rays, but datasets are still small compared to natural image datasets.
Supervision of abnormality localization has been shown to improve trained
models, partially compensating for dataset sizes. However, explicitly labeling
these anomalies requires an expert and is very time-consuming. We propose a
potentially scalable method for collecting implicit localization data using an
eye tracker to capture gaze locations and a microphone to capture a dictation
of a report, imitating …

arxiv data dataset localization reports tracking tracking data

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Risk Management - Machine Learning and Model Delivery Services, Product Associate - Senior Associate-

@ JPMorgan Chase & Co. | Wilmington, DE, United States

Senior ML Engineer (Speech/ASR)

@ ObserveAI | Bengaluru