一种基于深度学习的刨花板表面缺陷检测和识别方法

IF 2.2 3区 农林科学 Q1 MATERIALS SCIENCE, PAPER & WOOD
Chengliang Zhang, Chunling Wang, Liyuan Zhao, Xiaolong Qu, Xujie Gao
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引用次数: 0

摘要

刨花板是家具和其他木质工业产品的材料,直接影响最终产品的使用寿命。在这项研究中,一种创新的双抓取机制--"刨花板"--被广泛应用于家具和其他木质工业产品中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A method of particleboard surface defect detection and recognition based on deep learning
Particleboard is a material for furniture and other wooden industrial products, directly impacting the service life of the final product. In this study, an innovative dual-attention mechanism, the ...
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来源期刊
Wood Material Science & Engineering
Wood Material Science & Engineering Materials Science-General Materials Science
CiteScore
3.90
自引率
13.60%
发文量
131
审稿时长
79 days
期刊介绍: Wood Material Science and Engineering is a multidisciplinary and international journal with the aim to serve at the forefront of the wood science and technology field. The journal publishes original articles on basic and applied research dealing with: -Wood material science with emphasis on: water-wood relations, wood durability, wood modification, wood mechanics, wood composites, engineered wood products, energy conversion and eco-efficient wood based products. -Wood engineering, i.e. the application of the wood material science to designing, processing and manufacturing of forest products and the use of machines and processes for these products. Products of concern are biofuels, sawn wood and further refined products such as structural elements, interior fittings and furnishings. In this aspect the link between the nature of the wood material and the properties of the final wood products in-service and its impact on the environment is of outmost importance. High quality review papers may also be accepted but the topic should be discussed with the editor before submission.
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