25 citations · 26 across the 4 of their papers we have counts for
5 papers
Mixed-Prior Decision Risk for Open-Set Recognition
L. A. Erlygin, P. D. Proskura, A. A. Zaytsev
In open-set recognition (OSR), a probe must either be identified as one of the known gallery classes or rejected as unknown, so three error types coexist: false acceptance, false r…
Uncertainty Estimation for the Open-Set Text Classification systems
Leonid Erlygin, Alexey Zaytsev
Accurate uncertainty estimation is essential for building robust and trustworthy recognition systems. In this paper, we consider the open-set text classification (OSTC) task - and…
Holistic Uncertainty Estimation For Open-Set Recognition
Leonid Erlygin, Alexey Zaytsev
Accurate uncertainty estimation is a critical challenge in open-set recognition, where a probe biometric sample may belong to an unknown identity. It can be addressed through sampl…
Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust
Leonid Erlygin, Vladimir Zholobov, Valeriia Baklanova +2
Machine learning models play a vital role in time series forecasting. These models, however, often overlook an important element: point uncertainty estimates. Incorporating these e…
LSDNet: Trainable Modification of LSD Algorithm for Real-Time Line Segment Detection
Lev Teplyakov, Leonid Erlygin, Evgeny Shvets
As of today, the best accuracy in line segment detection (LSD) is achieved by algorithms based on convolutional neural networks - CNNs. Unfortunately, these methods utilize deep, h…