no code implementations • 4 May 2022 • Mayank Golhar, Taylor L. Bobrow, Saowanee Ngamruengphong, Nicholas J. Durr
This study demonstrates that synthetic colonoscopy images generated by Generative Adversarial Network (GAN) inversion can be used as training data to improve the lesion classification performance of deep learning models.
no code implementations • 7 Sep 2020 • Mayank Golhar, Taylor L. Bobrow, MirMilad Pourmousavi Khoshknab, Simran Jit, Saowanee Ngamruengphong, Nicholas J. Durr
While data-driven approaches excel at many image analysis tasks, the performance of these approaches is often limited by a shortage of annotated data available for training.