390 citations · 711 across the 7 of their papers we have counts for
7 papers
Face Recognition Using Synthetic Face Data
Omer Granoviter, Alexey Gruzdev, Vladimir Loginov +2
In the field of deep learning applied to face recognition, securing large-scale, high-quality datasets is vital for attaining precise and reliable results. However, amassing signif…
Knowing the Distance: Understanding the Gap Between Synthetic and Real Data For Face Parsing
Eli Friedman, Assaf Lehr, Alexey Gruzdev +4
The use of synthetic data for training computer vision algorithms has become increasingly popular due to its cost-effectiveness, scalability, and ability to provide accurate multi-…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
OpenFL: An open-source framework for Federated Learning
G Anthony Reina, Alexey Gruzdev, Patrick Foley +15
Federated learning (FL) is a computational paradigm that enables organizations to collaborate on machine learning (ML) projects without sharing sensitive data, such as, patient rec…
LPRNet: License Plate Recognition via Deep Neural Networks
Sergey Zherzdev, Alexey Gruzdev
This paper proposes LPRNet - end-to-end method for Automatic License Plate Recognition without preliminary character segmentation. Our approach is inspired by recent breakthroughs…