Search Results for author: Sergey I. Nikolenko

Found 8 papers, 2 papers with code

Benchmarking Multilabel Topic Classification in the Kyrgyz Language

1 code implementation30 Aug 2023 Anton Alekseev, Sergey I. Nikolenko, Gulnara Kabaeva

Kyrgyz is a very underrepresented language in terms of modern natural language processing resources.

Benchmarking Classification +2

Synthetic Data for Deep Learning

no code implementations25 Sep 2019 Sergey I. Nikolenko

Synthetic data is an increasingly popular tool for training deep learning models, especially in computer vision but also in other areas.

Autonomous Driving Domain Adaptation +2

AspeRa: Aspect-based Rating Prediction Model

no code implementations23 Jan 2019 Sergey I. Nikolenko, Elena Tutubalina, Valentin Malykh, Ilya Shenbin, Anton Alekseev

We propose a novel end-to-end Aspect-based Rating Prediction model (AspeRa) that estimates user rating based on review texts for the items and at the same time discovers coherent aspects of reviews that can be used to explain predictions or profile users.

Recommendation Systems

Adapting Convolutional Neural Networks for Geographical Domain Shift

no code implementations18 Jan 2019 Pavel Ostyakov, Sergey I. Nikolenko

We present the winning solution for the Inclusive Images Competition organized as part of the Conference on Neural Information Processing Systems (NeurIPS 2018) Competition Track.

SEIGAN: Towards Compositional Image Generation by Simultaneously Learning to Segment, Enhance, and Inpaint

no code implementations19 Nov 2018 Pavel Ostyakov, Roman Suvorov, Elizaveta Logacheva, Oleg Khomenko, Sergey I. Nikolenko

We present a novel approach to image manipulation and understanding by simultaneously learning to segment object masks, paste objects to another background image, and remove them from original images.

Generative Adversarial Network Image Generation +1

Label Denoising with Large Ensembles of Heterogeneous Neural Networks

no code implementations12 Sep 2018 Pavel Ostyakov, Elizaveta Logacheva, Roman Suvorov, Vladimir Aliev, Gleb Sterkin, Oleg Khomenko, Sergey I. Nikolenko

Despite recent advances in computer vision based on various convolutional architectures, video understanding remains an important challenge.

Data Augmentation Denoising +4

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