iOk Platform for Automated Object Detection and Analysis in Microscopy Images

Counting, measuring, and identifying particles is a crucial aspect of various research endeavors. Typically, images containing particles are manually processed using a software ruler. Automated processing techniques, which rely on conventional image processing methods such as edge detection and segm...

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Bibliographic Details
Main Authors: Kudinov, Vitalii Yu, Matveev, Andrey V., Nartova, Anna V., Sankova, Natalya N., Belotserkovskii, Valerii A., Okunev, Aleksey G.
Format: Conference Proceeding
Language:English
Subjects:
Chatbots
Codes
deep neural networks
machine learning
microscopy
Neural networks
particle recognition
Pattern recognition
Search problems
Software
Web services
Online Access:Request full text
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Summary:Counting, measuring, and identifying particles is a crucial aspect of various research endeavors. Typically, images containing particles are manually processed using a software ruler. Automated processing techniques, which rely on conventional image processing methods such as edge detection and segmentation, are not universally applicable and require setting several parameters through trial and error. Additionally, these techniques can only be utilized on high-quality images. Also, the ambiguity of the data set can greatly affect the quality of object identification. The report presents the iOk platform (iok.nsu.ru), which uses artificial intelligence through the ParticlesNN web service and Telegram bots DLgram and No Code ML as well as other means of detecting objects on an image. The platform provides automatic search and analysis of objects in images without pre-processing, regardless of the type and quality of the image. At the output, you can obtain information about object recognition, its area and size, as well as its position in the image. The neural network can be trained on user images, no programming skills are required. All the services are free.
ISSN:2473-8573
DOI:10.1109/APEIE59731.2023.10347794