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Auteurs principaux: Afonchikov, Danil, Kornaeva, Elena, Makovik, Irina, Kornaev, Alexey
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:https://arxiv.org/abs/2404.10319
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author Afonchikov, Danil
Kornaeva, Elena
Makovik, Irina
Kornaev, Alexey
author_facet Afonchikov, Danil
Kornaeva, Elena
Makovik, Irina
Kornaev, Alexey
contents Cells count become a challenging problem when the cells move in a continuous stream, and their boundaries are difficult for visual detection. To resolve this problem we modified the training and decision making processes using curriculum learning and multi-view predictions techniques, respectively.
format Preprint
id arxiv_https___arxiv_org_abs_2404_10319
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Application of Deep Learning Methods to Processing of Noisy Medical Video Data
Afonchikov, Danil
Kornaeva, Elena
Makovik, Irina
Kornaev, Alexey
Computer Vision and Pattern Recognition
Machine Learning
Cells count become a challenging problem when the cells move in a continuous stream, and their boundaries are difficult for visual detection. To resolve this problem we modified the training and decision making processes using curriculum learning and multi-view predictions techniques, respectively.
title Application of Deep Learning Methods to Processing of Noisy Medical Video Data
topic Computer Vision and Pattern Recognition
Machine Learning
url https://arxiv.org/abs/2404.10319