{"title":"IBD:基于深度学习的物联网大数据处理反馈框架","authors":"V. Mishra, Vivek Kumar, Neeraj Kumar Pandey","doi":"10.1109/SMART52563.2021.9675302","DOIUrl":null,"url":null,"abstract":"Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNNs)have the ability to find the accurate result in images and text respectively. The best classification results are still awaited due to the high cost of computation and high memory requirements of CNN and RNN. Our work suggests a framework that improves the quality of data at various layers by providing feedback to suggested system. The proposed framework leads to an error free processing system.","PeriodicalId":356096,"journal":{"name":"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"IBD: A Feedback Framework with Deep-learning for IoT-generated Big Data Processing\",\"authors\":\"V. Mishra, Vivek Kumar, Neeraj Kumar Pandey\",\"doi\":\"10.1109/SMART52563.2021.9675302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNNs)have the ability to find the accurate result in images and text respectively. The best classification results are still awaited due to the high cost of computation and high memory requirements of CNN and RNN. Our work suggests a framework that improves the quality of data at various layers by providing feedback to suggested system. The proposed framework leads to an error free processing system.\",\"PeriodicalId\":356096,\"journal\":{\"name\":\"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMART52563.2021.9675302\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMART52563.2021.9675302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
IBD: A Feedback Framework with Deep-learning for IoT-generated Big Data Processing
Convolutional Neural Network (CNN) and Recurrent Neural Networks (RNNs)have the ability to find the accurate result in images and text respectively. The best classification results are still awaited due to the high cost of computation and high memory requirements of CNN and RNN. Our work suggests a framework that improves the quality of data at various layers by providing feedback to suggested system. The proposed framework leads to an error free processing system.