1 code implementation • 31 Jul 2022 • Ivan Zakazov, Vladimir Shaposhnikov, Iaroslav Bespalov, Dmitry V. Dylov
Generalizability of deep learning models may be severely affected by the difference in the distributions of the train (source domain) and the test (target domain) sets, e. g., when the sets are produced by different hardware.
no code implementations • 2 Apr 2021 • Iaroslav Bespalov, Nazar Buzun, Oleg Kachan, Dmitry V. Dylov
Oftentimes, these methods either fail to produce enough new data or expand the dataset beyond the original knowledge domain.
no code implementations • 2 Oct 2020 • Viktor Shipitsin, Iaroslav Bespalov, Dmitry V. Dylov
We devise a universal adaptive neural layer to "learn" optimal frequency filter for each image together with the weights of the base neural network that performs some computer vision task.
no code implementations • 20 Jun 2020 • Iaroslav Bespalov, Nazar Buzun, Dmitry V. Dylov
Unsupervised retrieval of image features is vital for many computer vision tasks where the annotation is missing or scarce.