B. Rusyn, Y. Obukh, R. Kosarevych, O. Lutsyk, V. Korniy
{"title":"人工林分析与生态状况监测信息系统","authors":"B. Rusyn, Y. Obukh, R. Kosarevych, O. Lutsyk, V. Korniy","doi":"10.1109/aict52120.2021.9628990","DOIUrl":null,"url":null,"abstract":"This paper proposes information technology for analyzing the condition of forest plantations and monitoring the ecological condition of forests. Information technology is based on the proposed approach to automatic localization and recognition of affected trees, and is of great practical importance for environmental monitoring and forestry. A deep learning model has been developed for localization and recognition. This model consists of a detector and separate classifier modules. In order to train and validate the proposed network based on remote sensing images, a training database containing 9000 images was created. Comparison of the proposed model with existing methods is based on characteristics such as accuracy and speed. The accuracy and speed of the proposed recognition system was assessed on a validation sample of images, the size of which is 2000 images. To ensure real-time operation, the software is optimized to work with the GPU. The results of the work and the developed software are used in remote monitoring and classification systems for environmental monitoring and in applied tasks of forestry.","PeriodicalId":375013,"journal":{"name":"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Information System for Analysis of Forest Plantations and Monitoring of Ecological Condition\",\"authors\":\"B. Rusyn, Y. Obukh, R. Kosarevych, O. Lutsyk, V. Korniy\",\"doi\":\"10.1109/aict52120.2021.9628990\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes information technology for analyzing the condition of forest plantations and monitoring the ecological condition of forests. Information technology is based on the proposed approach to automatic localization and recognition of affected trees, and is of great practical importance for environmental monitoring and forestry. A deep learning model has been developed for localization and recognition. This model consists of a detector and separate classifier modules. In order to train and validate the proposed network based on remote sensing images, a training database containing 9000 images was created. Comparison of the proposed model with existing methods is based on characteristics such as accuracy and speed. The accuracy and speed of the proposed recognition system was assessed on a validation sample of images, the size of which is 2000 images. To ensure real-time operation, the software is optimized to work with the GPU. The results of the work and the developed software are used in remote monitoring and classification systems for environmental monitoring and in applied tasks of forestry.\",\"PeriodicalId\":375013,\"journal\":{\"name\":\"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)\",\"volume\":\"196 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/aict52120.2021.9628990\",\"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 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/aict52120.2021.9628990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Information System for Analysis of Forest Plantations and Monitoring of Ecological Condition
This paper proposes information technology for analyzing the condition of forest plantations and monitoring the ecological condition of forests. Information technology is based on the proposed approach to automatic localization and recognition of affected trees, and is of great practical importance for environmental monitoring and forestry. A deep learning model has been developed for localization and recognition. This model consists of a detector and separate classifier modules. In order to train and validate the proposed network based on remote sensing images, a training database containing 9000 images was created. Comparison of the proposed model with existing methods is based on characteristics such as accuracy and speed. The accuracy and speed of the proposed recognition system was assessed on a validation sample of images, the size of which is 2000 images. To ensure real-time operation, the software is optimized to work with the GPU. The results of the work and the developed software are used in remote monitoring and classification systems for environmental monitoring and in applied tasks of forestry.