Aditya Singh, Devesh Pandey, Anuj Pandey, S. Latam
{"title":"利用深度学习预测社会经济发展","authors":"Aditya Singh, Devesh Pandey, Anuj Pandey, S. Latam","doi":"10.46335/ijies.2023.8.4.2","DOIUrl":null,"url":null,"abstract":"— For Uniform growth across the country there is a need to find socio-economic status and monitoring of remote areas. It is about the current state of development or the process state of socio-economy of that place. In our paper, we will predict the development in an location using satellite images provided by various sources using a model that we create which will perform classification and use various image preprocessing techniques. The top things considered during monitoring are the roof top of houses, agriculture, water bodies and constructed roads etc. Convolution neural networks are known for its inbuilt libraries such as OpenCV, NumPy etc. OpenCV is good library has it known for increasing speed of process that is executing and also classifying the image. CNN also provides better accuracy for deep learning processes. In this paper we have use basically three modules:","PeriodicalId":286065,"journal":{"name":"International Journal of Innovations in Engineering and Science","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Socio-Economic Development Using Deep Learning\",\"authors\":\"Aditya Singh, Devesh Pandey, Anuj Pandey, S. Latam\",\"doi\":\"10.46335/ijies.2023.8.4.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"— For Uniform growth across the country there is a need to find socio-economic status and monitoring of remote areas. It is about the current state of development or the process state of socio-economy of that place. In our paper, we will predict the development in an location using satellite images provided by various sources using a model that we create which will perform classification and use various image preprocessing techniques. The top things considered during monitoring are the roof top of houses, agriculture, water bodies and constructed roads etc. Convolution neural networks are known for its inbuilt libraries such as OpenCV, NumPy etc. OpenCV is good library has it known for increasing speed of process that is executing and also classifying the image. CNN also provides better accuracy for deep learning processes. In this paper we have use basically three modules:\",\"PeriodicalId\":286065,\"journal\":{\"name\":\"International Journal of Innovations in Engineering and Science\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovations in Engineering and Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46335/ijies.2023.8.4.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovations in Engineering and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46335/ijies.2023.8.4.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predicting Socio-Economic Development Using Deep Learning
— For Uniform growth across the country there is a need to find socio-economic status and monitoring of remote areas. It is about the current state of development or the process state of socio-economy of that place. In our paper, we will predict the development in an location using satellite images provided by various sources using a model that we create which will perform classification and use various image preprocessing techniques. The top things considered during monitoring are the roof top of houses, agriculture, water bodies and constructed roads etc. Convolution neural networks are known for its inbuilt libraries such as OpenCV, NumPy etc. OpenCV is good library has it known for increasing speed of process that is executing and also classifying the image. CNN also provides better accuracy for deep learning processes. In this paper we have use basically three modules: