Analysis on the Current Status and Development of Industrial Instrument Equipment Detection Technology Based on Convolutional Neural Network

DOI

10.2991/978-94-6463-821-9_47How to use a DOI?

Keywords

Convolutional Neural Networks; Attention Mechanism; Feature Extraction Capabilities; Industrialization and Intelligence

Abstract

With the fast development of the Industry 4.0 program and the increasing popularity of high-level automation, the need for the identification and monitoring of industrial instruments grows as well. Convolutional neural networks can provide the precision and accuracy required for monitoring and recognition because of their powerful computing power and feature lock extraction, which can become a key technology to solve this problem. In this paper, the current status of digital automation monitoring of industrial instruments is reviewed by analyzing the real-life application cases of classical convolutional neural network models such as CRNN and YOLOv5 in industrial scenarios. According to the research, the application monitoring accuracy of CNN in complex industrial scenarios is excellent, but more research and results are needed in the lightweight of modules and the adaptability of multi-instrument equipment. In the future, the lightweight and highly efficient design of modules, multi-modal fusion technology, and self-supervised learning will be the main methods to help the industry system to be more intelligently advanced. This paper aims to offer technology suggestions to academia and industry, and motivate the industrial vision to improved.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Youkang Zhu
PY  - 2025
DA  - 2025/08/31
TI  - Analysis on the Current Status and Development of Industrial Instrument Equipment Detection Technology Based on Convolutional Neural Network
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 457
EP  - 465
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_47
DO  - 10.2991/978-94-6463-821-9_47
ID  - Zhu2025
ER  -