{"title":"卷积神经网络(CNN)的发展与应用综述","authors":"Sandeep Joshi, M. Manu, Amit Mittal","doi":"10.1109/ICECAA58104.2023.10212250","DOIUrl":null,"url":null,"abstract":"Within this literary document, a panoramic insight is presented on the progression and practical uses of Convolutional Neural Networks (CNNs), an influential technique in deep learning that serves as a major element within computer vision research alongside other areas. Through a comprehensive analysis of the literature, this research study presents thehistorical development of CNNs from early work on perceptrons to current state-of-the-art architectures like VGGNet, ResNet, and EfficientNet. The review highlights the key contributions of CNNs in various fields, such as image and video recognition, natural language processing, and audio analysis. Furthermore, it discusses the potential for further research and development of CNNs, including the challenges in training and optimizing CNNs and the future directions of CNNs. Overall, this review underscores the importance of CNNs in enabling breakthroughsin diverse fields and their potential for continued impact on the scientific community.","PeriodicalId":114624,"journal":{"name":"2023 2nd International Conference on Edge Computing and Applications (ICECAA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review of the Evolution and Applications of Convolutional Neural Network (CNN)\",\"authors\":\"Sandeep Joshi, M. Manu, Amit Mittal\",\"doi\":\"10.1109/ICECAA58104.2023.10212250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Within this literary document, a panoramic insight is presented on the progression and practical uses of Convolutional Neural Networks (CNNs), an influential technique in deep learning that serves as a major element within computer vision research alongside other areas. Through a comprehensive analysis of the literature, this research study presents thehistorical development of CNNs from early work on perceptrons to current state-of-the-art architectures like VGGNet, ResNet, and EfficientNet. The review highlights the key contributions of CNNs in various fields, such as image and video recognition, natural language processing, and audio analysis. Furthermore, it discusses the potential for further research and development of CNNs, including the challenges in training and optimizing CNNs and the future directions of CNNs. Overall, this review underscores the importance of CNNs in enabling breakthroughsin diverse fields and their potential for continued impact on the scientific community.\",\"PeriodicalId\":114624,\"journal\":{\"name\":\"2023 2nd International Conference on Edge Computing and Applications (ICECAA)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 2nd International Conference on Edge Computing and Applications (ICECAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECAA58104.2023.10212250\",\"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 2nd International Conference on Edge Computing and Applications (ICECAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECAA58104.2023.10212250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Review of the Evolution and Applications of Convolutional Neural Network (CNN)
Within this literary document, a panoramic insight is presented on the progression and practical uses of Convolutional Neural Networks (CNNs), an influential technique in deep learning that serves as a major element within computer vision research alongside other areas. Through a comprehensive analysis of the literature, this research study presents thehistorical development of CNNs from early work on perceptrons to current state-of-the-art architectures like VGGNet, ResNet, and EfficientNet. The review highlights the key contributions of CNNs in various fields, such as image and video recognition, natural language processing, and audio analysis. Furthermore, it discusses the potential for further research and development of CNNs, including the challenges in training and optimizing CNNs and the future directions of CNNs. Overall, this review underscores the importance of CNNs in enabling breakthroughsin diverse fields and their potential for continued impact on the scientific community.