{"title":"基于CNN的移动灵长类动物图像识别","authors":"Nuruddin Wiranda, A. E. Putra","doi":"10.22146/ijccs.65640","DOIUrl":null,"url":null,"abstract":"Six out of 25 species of primates most endangered are in Indonesia. Six of these primates are namely Orangutan, Lutung, Bekantan, Tarsius tumpara, Kukang, and Simakobu. Three of the six primates live mostly on the island of Borneo. One form of preservation of primate treasures found in Kalimantan is by conducting studies on primate identification. In this study, an android app was developed using the CNN method to identify primate species in Kalimantan wetlands. CNN is used to extract spatial features from primate images to be very efficient for image identification problems. The data set used in this study is ImageNets, while the model used is MobileNets. The application was tested using two scenarios, namely using photos and video recordings. Photos were taken directly, then reduced to a resolution of 256 x 256. Then, videos were taken in approximately 10 to 30 seconds with two megapixel camera resolution. The results obtained was an average accuracy of 93.6% when using photos and 79% when using video recordings. After calculating the accuracy, the usability test using SUS was performed. Based on the SUS results, it is known that the application developed is feasible to use.","PeriodicalId":31625,"journal":{"name":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Mobile-based Primate Image Recognition using CNN\",\"authors\":\"Nuruddin Wiranda, A. E. Putra\",\"doi\":\"10.22146/ijccs.65640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Six out of 25 species of primates most endangered are in Indonesia. Six of these primates are namely Orangutan, Lutung, Bekantan, Tarsius tumpara, Kukang, and Simakobu. Three of the six primates live mostly on the island of Borneo. One form of preservation of primate treasures found in Kalimantan is by conducting studies on primate identification. In this study, an android app was developed using the CNN method to identify primate species in Kalimantan wetlands. CNN is used to extract spatial features from primate images to be very efficient for image identification problems. The data set used in this study is ImageNets, while the model used is MobileNets. The application was tested using two scenarios, namely using photos and video recordings. Photos were taken directly, then reduced to a resolution of 256 x 256. Then, videos were taken in approximately 10 to 30 seconds with two megapixel camera resolution. The results obtained was an average accuracy of 93.6% when using photos and 79% when using video recordings. After calculating the accuracy, the usability test using SUS was performed. Based on the SUS results, it is known that the application developed is feasible to use.\",\"PeriodicalId\":31625,\"journal\":{\"name\":\"IJCCS Indonesian Journal of Computing and Cybernetics Systems\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IJCCS Indonesian Journal of Computing and Cybernetics Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22146/ijccs.65640\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IJCCS Indonesian Journal of Computing and Cybernetics Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22146/ijccs.65640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
25种最濒危的灵长类动物中有6种在印度尼西亚。这些灵长类动物中有六种,即猩猩、鲁通、贝坎坦、Tarsius tumpara、Kukang和Simakobu。六种灵长类动物中有三种主要生活在婆罗洲岛上。加里曼丹发现的灵长类动物宝藏的一种保存方式是进行灵长类动物鉴定研究。在这项研究中,使用CNN方法开发了一款安卓应用程序,用于识别加里曼丹湿地的灵长类动物物种。CNN用于从灵长类动物图像中提取空间特征,这对于图像识别问题非常有效。本研究中使用的数据集是ImageNets,而使用的模型是MobileNets。该应用程序使用两种场景进行了测试,即使用照片和视频录制。照片是直接拍摄的,然后缩小到256 x 256的分辨率。然后,用200万像素的摄像机分辨率在大约10到30秒内拍摄视频。使用照片时获得的结果的平均准确率为93.6%,使用视频记录时获得的平均准确度为79%。在计算精度之后,使用SUS进行可用性测试。基于SUS结果,已知所开发的应用程序是可行的。
Six out of 25 species of primates most endangered are in Indonesia. Six of these primates are namely Orangutan, Lutung, Bekantan, Tarsius tumpara, Kukang, and Simakobu. Three of the six primates live mostly on the island of Borneo. One form of preservation of primate treasures found in Kalimantan is by conducting studies on primate identification. In this study, an android app was developed using the CNN method to identify primate species in Kalimantan wetlands. CNN is used to extract spatial features from primate images to be very efficient for image identification problems. The data set used in this study is ImageNets, while the model used is MobileNets. The application was tested using two scenarios, namely using photos and video recordings. Photos were taken directly, then reduced to a resolution of 256 x 256. Then, videos were taken in approximately 10 to 30 seconds with two megapixel camera resolution. The results obtained was an average accuracy of 93.6% when using photos and 79% when using video recordings. After calculating the accuracy, the usability test using SUS was performed. Based on the SUS results, it is known that the application developed is feasible to use.