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20152022
most citedTwo-phase approaches to optimal model-based design of experiments: how many experiments and which ones?

30 citations · 190 across the 36 of their papers we have counts for

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8 papers · 1 filter

cs.CV20222 cited

Hyperbolic Vision Transformers: Combining Improvements in Metric Learning

Aleksandr Ermolov, Leyla Mirvakhabova, Valentin Khrulkov +2

Metric learning aims to learn a highly discriminative model encouraging the embeddings of similar classes to be close in the chosen metrics and pushed apart for dissimilar ones. Th…

cs.CV2021

Generation of the NIR spectral Band for Satellite Images with Convolutional Neural Networks

Svetlana Illarionova, Dmitrii Shadrin, Alexey Trekin +2

The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote sensing imagery provides vital information for the landcover classification, especially con…

cs.CV20202 cited

Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network

Anh-Huy Phan, Konstantin Sobolev, Konstantin Sozykin +6

Most state of the art deep neural networks are overparameterized and exhibit a high computational cost. A straightforward approach to this problem is to replace convolutional kerne…

cs.CV20201 cited

Bayesian aggregation improves traditional single image crop classification approaches

Ivan Matvienko, Mikhail Gasanov, Anna Petrovskaia +3

Machine learning (ML) methods and neural networks (NN) are widely implemented for crop types recognition and classification based on satellite images. However, most of these studie…

cs.CV2019

Recognition of Russian traffic signs in winter conditions. Solutions of the "Ice Vision" competition winners

Artem L. Pavlov, Azat Davletshin, Alexey Kharlamov +8

With the advancements of various autonomous car projects aiming to achieve SAE Level 5, real-time detection of traffic signs in real-life scenarios has become a highly relevant pro…

cs.CV2019

Hyperbolic Image Embeddings

Valentin Khrulkov, Leyla Mirvakhabova, Evgeniya Ustinova +2

Computer vision tasks such as image classification, image retrieval and few-shot learning are currently dominated by Euclidean and spherical embeddings, so that the final decisions…