Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model

Wentao Chen

doi:10.47297/wspbtsWSP2755-952103.20240202

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Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model

2卷第2期

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Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model
Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model
Nanjing University of Posts and Telecommunications, NJUPT, Nanjing, China 210023
2024年2卷第2期页码：14-18
纸质出版日期：2024-12-24
DOI：10.47297/wspbtsWSP2755-952103.20240202
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(2024). Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model. 分析测试学报, 2(2), 14-18.

Chen Wentao.Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model[J].Biomedical Testing & Sensing,2024,02(02):14-18.
(2024). Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model. 分析测试学报, 2(2), 14-18. DOI： 10.47297/wspbtsWSP2755-952103.20240202.

Chen Wentao.Algorithm for Lightweight Mineral Recognition Based on Improved Neural Network Model[J].Biomedical Testing & Sensing,2024,02(02):14-18. DOI： 10.47297/wspbtsWSP2755-952103.20240202.

摘要

Abstract

This study explores the potential of deep learning in mineral identification and addresses the challenge of deploying large neural network models on embedded devices. To achieve this

I propose a lightweight algorithm that maintains accuracy while reducing the model's storage space and computational load.

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Keywords

references

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