{"title":"Faster RCNN Algorithm for Object Detection and Thereby provides a way for Tile Grading","authors":"D.A.I.S Sewwandi, D. Vidanagama","doi":"10.1109/SLAAI-ICAI56923.2022.10002633","DOIUrl":null,"url":null,"abstract":"Nowadays, each industry uses different kinds of smart appliances to make their day-to-day tasks easy. Because of the emergence of new technologies, one of those affected industries is the manufacturing industry which has a major concern about automating the manufacturing processes to provide quality-assured products on time. Among the production companies, tile manufacturing is facing a huge problem in the process of quality checking. Although the whole manufacturing process is automated, quality checking has a manual process. Because of the human involvement in this process, it occurs mistakes when it tries to do mass production based on the demand. So this study attempts on bringing a novel way for the existing manual tile grading mechanism using newer technology in deep learning, the object detection in the computer vision area to bring a novel outcome.","PeriodicalId":308901,"journal":{"name":"2022 6th SLAAI International Conference on Artificial Intelligence (SLAAI-ICAI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 6th SLAAI International Conference on Artificial Intelligence (SLAAI-ICAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SLAAI-ICAI56923.2022.10002633","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Nowadays, each industry uses different kinds of smart appliances to make their day-to-day tasks easy. Because of the emergence of new technologies, one of those affected industries is the manufacturing industry which has a major concern about automating the manufacturing processes to provide quality-assured products on time. Among the production companies, tile manufacturing is facing a huge problem in the process of quality checking. Although the whole manufacturing process is automated, quality checking has a manual process. Because of the human involvement in this process, it occurs mistakes when it tries to do mass production based on the demand. So this study attempts on bringing a novel way for the existing manual tile grading mechanism using newer technology in deep learning, the object detection in the computer vision area to bring a novel outcome.