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Research on Gear Image Classification Algorithm

Published: 09 July 2024 Publication History

Abstract

In the process of simulating printing gear image, the error algorithm has deviation, which results in the jitter phenomenon of the printed gear image. According to the degree of jitter, gear images can be divided into qualified and defective products. How to design a high recognition rate image classification method based on machine vision technology is the focus of this paper. This paper presents a convolutional neural network image classification model, which consists of convolution layer, maximum pool layer, Flatten, Dense layer, etc. The model receives pre-operation images such as binary image processing as training samples. The experimental results show that the classification accuracy of the network for gear image is 100%, and the expected goal is achieved.

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AIMSCM '23: Proceedings of the 2023 International Conference on AI and Metaverse in Supply Chain Management
November 2023
239 pages
ISBN:9798400708251
DOI:10.1145/3648050
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 July 2024

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Author Tags

  1. Convolutional neural network (CNN)
  2. Deep learning
  3. Gear image classification

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • Hunan Provincial Natural Science Foundatio

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AIMSCM '23

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