150 citations · 424 across the 27 of their papers we have counts for
7 papers · 1 filter
Optimal MRI Undersampling Patterns for Ultimate Benefit of Medical Vision Tasks
Artem Razumov, Oleg Y. Rogov, Dmitry V. Dylov
To accelerate MRI, the field of compressed sensing is traditionally concerned with optimizing the image quality after a partial undersampling of the measurable -space.…
DASHA: Decentralized Autofocusing System with Hierarchical Agents
Anna Anikina, Oleg Y. Rogov, Dmitry V. Dylov
State-of-the-art object detection models are frequently trained offline using available datasets, such as ImageNet: large and overly diverse data that are unbalanced and hard to cl…
Strong Gaussian Approximation for the Sum of Random Vectors
Nazar Buzun, Nikolay Shvetsov, Dmitry V. Dylov
This paper derives a new strong Gaussian approximation bound for the sum of independent random vectors. The approach relies on the optimal transport theory and yields \textit{expli…
Landmarks Augmentation with Manifold-Barycentric Oversampling
Iaroslav Bespalov, Nazar Buzun, Oleg Kachan +1
The training of Generative Adversarial Networks (GANs) requires a large amount of data, stimulating the development of new augmentation methods to alleviate the challenge. Oftentim…
Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
Aleksandr Belov, Joel Stadelmann, Sergey Kastryulin +1
We went below the MRI acceleration factors (a.k.a., k-space undersampling) reported by all published papers that reference the original fastMRI challenge, and then considered power…
Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates
Artem Shelmanov, Dmitri Puzyrev, Lyubov Kupriyanova +7
Annotating training data for sequence tagging of texts is usually very time-consuming. Recent advances in transfer learning for natural language processing in conjunction with acti…
No-reference denoising of low-dose CT projections
Elvira Zainulina, Alexey Chernyavskiy, Dmitry V. Dylov
Low-dose computed tomography (LDCT) became a clear trend in radiology with an aspiration to refrain from delivering excessive X-ray radiation to the patients. The reduction of the…