Jay Sanghvi, Jay Rathod, Sakshi Nemade, Hasti Panchal, A. Pavate
{"title":"使用机器学习算法的标志检测:综述","authors":"Jay Sanghvi, Jay Rathod, Sakshi Nemade, Hasti Panchal, A. Pavate","doi":"10.1109/CSCITA55725.2023.10105056","DOIUrl":null,"url":null,"abstract":"As more and more logos are produced, logo detection has gradually grown in popularity as study across numerous jobs and sectors. Deep learning-based solutions, which make use of numerous data sets,learning techniques, network designs, etc., have dominated recent advancements in this field. This research examines the progress made in the field of logo detection using deep learning approaches. In order to evaluate the efficacy of logo detection algorithms, which tend to be more diversified, difficult, and realistically reflective of real life, we first discuss a thorough background of the topic. The pros and disadvantages of each learning approach are then thoroughly analysed, along with the current logo detection strategies.To wrap up this study, we examine probable obstacles and provide the future directions for logo detecting development.","PeriodicalId":224479,"journal":{"name":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Logo Detection Using Machine Learning Algorithm : A Survey\",\"authors\":\"Jay Sanghvi, Jay Rathod, Sakshi Nemade, Hasti Panchal, A. Pavate\",\"doi\":\"10.1109/CSCITA55725.2023.10105056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As more and more logos are produced, logo detection has gradually grown in popularity as study across numerous jobs and sectors. Deep learning-based solutions, which make use of numerous data sets,learning techniques, network designs, etc., have dominated recent advancements in this field. This research examines the progress made in the field of logo detection using deep learning approaches. In order to evaluate the efficacy of logo detection algorithms, which tend to be more diversified, difficult, and realistically reflective of real life, we first discuss a thorough background of the topic. The pros and disadvantages of each learning approach are then thoroughly analysed, along with the current logo detection strategies.To wrap up this study, we examine probable obstacles and provide the future directions for logo detecting development.\",\"PeriodicalId\":224479,\"journal\":{\"name\":\"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCITA55725.2023.10105056\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Communication System, Computing and IT Applications (CSCITA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCITA55725.2023.10105056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Logo Detection Using Machine Learning Algorithm : A Survey
As more and more logos are produced, logo detection has gradually grown in popularity as study across numerous jobs and sectors. Deep learning-based solutions, which make use of numerous data sets,learning techniques, network designs, etc., have dominated recent advancements in this field. This research examines the progress made in the field of logo detection using deep learning approaches. In order to evaluate the efficacy of logo detection algorithms, which tend to be more diversified, difficult, and realistically reflective of real life, we first discuss a thorough background of the topic. The pros and disadvantages of each learning approach are then thoroughly analysed, along with the current logo detection strategies.To wrap up this study, we examine probable obstacles and provide the future directions for logo detecting development.