Artificial intelligence for imaging data analysis in materials science: microscopy and behind

Autor:	Aleksey G. Okunev, A. V. Matveev, M. Yu Mashukov, N N Sankova, Anna V. Nartova
Rok vydání:	2021
Předmět:	Mode (computer interface) Computer engineering Microscopy Code (cryptography) Deep neural networks Imaging data Task (project management)
Zdroj:	IOP Conference Series: Materials Science and Engineering. 1155:012015
ISSN:	1757-899X 1757-8981
DOI:	10.1088/1757-899x/1155/1/012015
Popis:	In various fields of microscopy, a fairly common task is to count and determine the size of the studied objects. Sometimes this is a one-time tedious task that is done by lab personnel without the programming skills. In this paper, we present an approach that allows researchers to perform automated processing of research imaging data using our services and even to train deep neural networks on their own in no code mode.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::3d954bcb0bb8577584c1b894286e54e0 https://doi.org/10.1088/1757-899x/1155/1/012015 Zobrazit plný text záznamu