63 citations · 64 across the 3 of their papers we have counts for
3 papers
Survey of Deep Learning Methods for Inverse Problems
Shima Kamyab, Zohreh Azimifar, Rasool Sabzi +1
In this paper we investigate a variety of deep learning strategies for solving inverse problems. We classify existing deep learning solutions for inverse problems into three catego…
PathoNet: Deep learning assisted evaluation of Ki-67 and tumor infiltrating lymphocytes (TILs) as prognostic factors in breast cancer; A large dataset and baseline
Farzin Negahbani, Rasool Sabzi, Bita Pakniyat Jahromi +5
The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as prognostic factors in predicting tumor progression and its treatment response. The value…
Deep Generative Models: Deterministic Prediction with an Application in Inverse Rendering
Shima Kamyab, Rasool Sabzi, Zohreh Azimifar
Deep generative models are stochastic neural networks capable of learning the distribution of data so as to generate new samples. Conditional Variational Autoencoder (CVAE) is a po…