{"title":"利用机器学习和OCR验证技术识别基于可见包装特征的产品类别","authors":"Takorn Prexawanprasut, Lalita Santiworarak, Piyaporn Nurarak, Poom Juasiripukdee","doi":"10.1145/3589572.3589589","DOIUrl":null,"url":null,"abstract":"Customs clearance is a challenging and time-consuming process that must be completed in the sphere of international trade. As a result, the cargo is frequently delayed at the port. If the personnel know the initial number of items, they may be able to continue with other procedures even when they are not physically present at the location. Image processing is helpful in this area since it allows for the prediction of the type of goods based on the appearance of the package. This allows for the determination of the quantity of each type of product prior to the arrival of the employees at the site. Three distinct import-export companies contributed 5,675 photos, and a machine learning approach was used to create a model that can predict the types of things that fall into one of five categories. Also, the researchers made an OCR-based classification algorithm with the goal of making machine learning work better for certain types of things that have trouble learning.","PeriodicalId":296325,"journal":{"name":"Proceedings of the 2023 6th International Conference on Machine Vision and Applications","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Employing Machine Learning and an OCR Validation Technique to Identify Product Category Based on Visible Packaging Features\",\"authors\":\"Takorn Prexawanprasut, Lalita Santiworarak, Piyaporn Nurarak, Poom Juasiripukdee\",\"doi\":\"10.1145/3589572.3589589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Customs clearance is a challenging and time-consuming process that must be completed in the sphere of international trade. As a result, the cargo is frequently delayed at the port. If the personnel know the initial number of items, they may be able to continue with other procedures even when they are not physically present at the location. Image processing is helpful in this area since it allows for the prediction of the type of goods based on the appearance of the package. This allows for the determination of the quantity of each type of product prior to the arrival of the employees at the site. Three distinct import-export companies contributed 5,675 photos, and a machine learning approach was used to create a model that can predict the types of things that fall into one of five categories. Also, the researchers made an OCR-based classification algorithm with the goal of making machine learning work better for certain types of things that have trouble learning.\",\"PeriodicalId\":296325,\"journal\":{\"name\":\"Proceedings of the 2023 6th International Conference on Machine Vision and Applications\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2023 6th International Conference on Machine Vision and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3589572.3589589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2023 6th International Conference on Machine Vision and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3589572.3589589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Employing Machine Learning and an OCR Validation Technique to Identify Product Category Based on Visible Packaging Features
Customs clearance is a challenging and time-consuming process that must be completed in the sphere of international trade. As a result, the cargo is frequently delayed at the port. If the personnel know the initial number of items, they may be able to continue with other procedures even when they are not physically present at the location. Image processing is helpful in this area since it allows for the prediction of the type of goods based on the appearance of the package. This allows for the determination of the quantity of each type of product prior to the arrival of the employees at the site. Three distinct import-export companies contributed 5,675 photos, and a machine learning approach was used to create a model that can predict the types of things that fall into one of five categories. Also, the researchers made an OCR-based classification algorithm with the goal of making machine learning work better for certain types of things that have trouble learning.