{"title":"航拍图像中牡蛎架的自动识别","authors":"Wu-Ja Lin, Yi-Xiang Huang","doi":"10.1109/ISSNIP.2014.6827688","DOIUrl":null,"url":null,"abstract":"In this manuscript, we propose a system which can automatically recognize the oyster racks in an aerial image. As the oyster racks are recognized, the volume of the oysters could thus be estimated and the price can be predicted in advance. Besides that, when a disaster such as a typhoon strikes on the offshore, the loss could also be estimated when the numbers of oyster racks before and after the disaster are available for analysis. These information are useful for the local government in governing the aquaculture affairs. The advantage of the proposed system is to provide a useful tool in analyzing aquaculture information with less man power and time.","PeriodicalId":269784,"journal":{"name":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Automatic recognition of oyster racks in the aerial image\",\"authors\":\"Wu-Ja Lin, Yi-Xiang Huang\",\"doi\":\"10.1109/ISSNIP.2014.6827688\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this manuscript, we propose a system which can automatically recognize the oyster racks in an aerial image. As the oyster racks are recognized, the volume of the oysters could thus be estimated and the price can be predicted in advance. Besides that, when a disaster such as a typhoon strikes on the offshore, the loss could also be estimated when the numbers of oyster racks before and after the disaster are available for analysis. These information are useful for the local government in governing the aquaculture affairs. The advantage of the proposed system is to provide a useful tool in analyzing aquaculture information with less man power and time.\",\"PeriodicalId\":269784,\"journal\":{\"name\":\"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSNIP.2014.6827688\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSNIP.2014.6827688","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic recognition of oyster racks in the aerial image
In this manuscript, we propose a system which can automatically recognize the oyster racks in an aerial image. As the oyster racks are recognized, the volume of the oysters could thus be estimated and the price can be predicted in advance. Besides that, when a disaster such as a typhoon strikes on the offshore, the loss could also be estimated when the numbers of oyster racks before and after the disaster are available for analysis. These information are useful for the local government in governing the aquaculture affairs. The advantage of the proposed system is to provide a useful tool in analyzing aquaculture information with less man power and time.