{"title":"语义分割的卷积神经网络研究进展","authors":"Abdelrahman Kaseb, Mahmoud Khaled, Omar Galal","doi":"10.1109/ACIT57182.2022.9994096","DOIUrl":null,"url":null,"abstract":"Image segmentation is one of the most researched problems in computer vision. Various algorithms and techniques in artificial intelligence and machine learning were used and experimented with. Recently deep learning models have improved state-of-the-art performance on most of the well-known semantic segmentation datasets. In this work, we present a comprehensive study of 9 of the most recent models and methods in semantic segmentation. We experiment with these models on different datasets and draw our conclusions.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Convolutional Neural Networks for Semantic Segmentation: A Recent Survey\",\"authors\":\"Abdelrahman Kaseb, Mahmoud Khaled, Omar Galal\",\"doi\":\"10.1109/ACIT57182.2022.9994096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image segmentation is one of the most researched problems in computer vision. Various algorithms and techniques in artificial intelligence and machine learning were used and experimented with. Recently deep learning models have improved state-of-the-art performance on most of the well-known semantic segmentation datasets. In this work, we present a comprehensive study of 9 of the most recent models and methods in semantic segmentation. We experiment with these models on different datasets and draw our conclusions.\",\"PeriodicalId\":256713,\"journal\":{\"name\":\"2022 International Arab Conference on Information Technology (ACIT)\",\"volume\":\"89 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Arab Conference on Information Technology (ACIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACIT57182.2022.9994096\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Arab Conference on Information Technology (ACIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACIT57182.2022.9994096","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convolutional Neural Networks for Semantic Segmentation: A Recent Survey
Image segmentation is one of the most researched problems in computer vision. Various algorithms and techniques in artificial intelligence and machine learning were used and experimented with. Recently deep learning models have improved state-of-the-art performance on most of the well-known semantic segmentation datasets. In this work, we present a comprehensive study of 9 of the most recent models and methods in semantic segmentation. We experiment with these models on different datasets and draw our conclusions.