Open AccessArtificial intelligence for imaging data analysis in materials science: microscopy and behind
Author(s) -
A. G. Okunev,
Mikhail Yu. Mashukov,
Natalya Sankova,
Anna V. Nartova,
А. В. Матвеев
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1155/1/012015
Subject(s) - task (project management) , computer science , artificial intelligence , artificial neural network , deep learning , microscopy , code (set theory) , data science , engineering , programming language , optics , systems engineering , physics , set (abstract data type)
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.