45 citations · 49 across the 5 of their papers we have counts for
5 papers
Artificial intelligence as a gateway to scientific discovery: Uncovering features in retinal fundus images
Parsa Delavari, Gulcenur Ozturan, Ozgur Yilmaz +1
Purpose: Convolutional neural networks can be trained to detect various conditions or patient traits based on retinal fundus photographs, some of which, such as the patient sex, ar…
Learning from few examples: Classifying sex from retinal images via deep learning
Aaron Berk, Gulcenur Ozturan, Parsa Delavari +3
Deep learning has seen tremendous interest in medical imaging, particularly in the use of convolutional neural networks (CNNs) for developing automated diagnostic tools. The facili…
A coherence parameter characterizing generative compressed sensing with Fourier measurements
Aaron Berk, Simone Brugiapaglia, Babhru Joshi +3
In Bora et al. (2017), a mathematical framework was developed for compressed sensing guarantees in the setting where the measurement matrix is Gaussian and the signal structure is…
On the best choice of Lasso program given data parameters
Aaron Berk, Yaniv Plan, Özgür Yilmaz
Generalized compressed sensing (GCS) is a paradigm in which a structured high-dimensional signal may be recovered from random, under-determined, and corrupted linear measurements.…
Sensitivity of minimization to parameter choice
Aaron Berk, Yaniv Plan, Özgür Yilmaz
The use of generalized LASSO is a common technique for recovery of structured high-dimensional signals. Each generalized LASSO program has a governing parameter whose optimal value…