DEVELOPMENT OF A VIRTUAL LABORATORY FOR CONVOLUTIONAL NEURAL NETWORKS

The article examines the potential for modernising the process of learning and research in the field of convolutional neural networks (CNN). The authors describe the architecture and functional capabilities of a laboratory that enables experimentation with various CNN parameters, significantly simplifying the learning and mastery of this technology. The virtual environment provides students with the opportunity to work with real data, visualise and analyse results without the need for expensive equipment. The laboratory also offers integration with databases, making it possible to store results in the system for future use.

Authors

Publication Details

Journal
Научное мнение
Published
2024-12-29
DOI
https://doi.org/10.25807/22224378_2024_12_107
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DEVELOPMENT OF A VIRTUAL LABORATORY FOR CONVOLUTIONAL NEURAL NETWORKS

Darya Vasilieva, I. A. KUDRYAVTSEVA
Научное мнение
Experimental Learning in Engineering
article

DEVELOPMENT OF A VIRTUAL LABORATORY FOR CONVOLUTIONAL NEURAL NETWORKS

Darya Vasilieva, I. A. KUDRYAVTSEVA
article en

Abstract

The article examines the potential for modernising the process of learning and research in the field of convolutional neural networks (CNN). The authors describe the architecture and functional capabilities of a laboratory that enables experimentation with various CNN parameters, significantly simplifying the learning and mastery of this technology. The virtual environment provides students with the opportunity to work with real data, visualise and analyse results without the need for expensive equipment. The laboratory also offers integration with databases, making it possible to store results in the system for future use.

Научное мнение(12)
Openalex Percentile: Top 62%
Experimental Learning in Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.