{"title":"一种基于深度学习的刨花板表面缺陷检测和识别方法","authors":"Chengliang Zhang, Chunling Wang, Liyuan Zhao, Xiaolong Qu, Xujie Gao","doi":"10.1080/17480272.2024.2323579","DOIUrl":null,"url":null,"abstract":"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 ...","PeriodicalId":48567,"journal":{"name":"Wood Material Science & Engineering","volume":"6 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2024-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A method of particleboard surface defect detection and recognition based on deep learning\",\"authors\":\"Chengliang Zhang, Chunling Wang, Liyuan Zhao, Xiaolong Qu, Xujie Gao\",\"doi\":\"10.1080/17480272.2024.2323579\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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 ...\",\"PeriodicalId\":48567,\"journal\":{\"name\":\"Wood Material Science & Engineering\",\"volume\":\"6 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-03-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wood Material Science & Engineering\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1080/17480272.2024.2323579\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, PAPER & WOOD\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wood Material Science & Engineering","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1080/17480272.2024.2323579","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, PAPER & WOOD","Score":null,"Total":0}
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 ...
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.