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Akademický článek

Transformer-Based Deep Monocular Visual Odometry for Edge Devices

Autor: Anton Klochkov, Ivan Drokin

Publikováno v: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 31, Iss 2, Pp 422-428 (2022)

A lot of recent works have shown that deep learning-based visual odometry methods outperform existing feature-based approaches in the monocular case. However, most of them cannot be used in mobile robotics because they require a sufficiently powerful

Externí odkaz: https://doaj.org/article/5c1e8879b64b480c8b2935889a4d4d4b

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End-to-End Lung Nodule Detection Framework with Model-Based Feature Projection Block

Autor: Elena Ericheva, Ivan Drokin

Publikováno v: Machine Learning in Medical Imaging ISBN: 9783030875886
MLMI@MICCAI

This paper proposes novel end-to-end framework for detecting suspicious pulmonary nodules in chest CT scans. The method’s core idea is a new nodule segmentation architecture with a model-based feature projection block on three-dimensional convoluti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::045b6d1bcc363f95752dc6673a9145b3
https://doi.org/10.1007/978-3-030-87589-3_10

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Deep Learning on Point Clouds for False Positive Reduction at Nodule Detection in Chest CT Scans

Autor: Ivan Drokin, Elena Ericheva

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030726096
AIST

This paper focuses on a novel approach for false-positive reduction (FPR) of nodule candidates in Computer-Aided Detection (CADe) systems following the suspicious lesions detection stage. Contrary to typical decisions in medical image analysis, the p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2542d9647d484ca1f87e602bdb48c517
https://doi.org/10.1007/978-3-030-72610-2_15

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Data Augmentation with GAN: Improving Chest X-Ray Pathologies Prediction on Class-Imbalanced Cases

Autor: Ivan Drokin, Tatiana Malygina, Elena Ericheva

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030373337
AIST

When one applies machine learning to a real-world problem, sometimes data imbalance makes a crucial impact on the resulting model’s performance. We propose to use generative adversarial network (GAN) to do data balancing through data augmentation i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e34cf547c90e90007b0ed13f343b4c0c
https://doi.org/10.1007/978-3-030-37334-4_29

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A Model-Free Comorbidities-Based Events Prediction in ICU Unit

Autor: Ivan Drokin, Tatiana Malygina

Publikováno v: Communications in Computer and Information Science ISBN: 9783030012038

In this work we focus on recently introduced “medical concept vectors” (MCV) extracted from electronic health records (EHR), explore in similar manner several methods useful for patient’s medical history events prediction and provide our own no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::146c6fb89947eeda2328ae7ad3d61f3e
https://doi.org/10.1007/978-3-030-01204-5_10

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Computer realization of the hybrid algorithm of search of an extremum

Autor: Ivan Drokin

Publikováno v: 2014 International Conference on Computer Technologies in Physical and Engineering Applications (ICCTPEA).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::182a358673b51ba018d846bd72dc2a3e
https://doi.org/10.1109/icctpea.2014.6893265

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