文章詳目資料

Journal of Computers EIMEDLINEScopus

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篇名 Using Deep Learning to Track Stray Animals with Mobile Device
卷期 32:1
作者 Rung-Ching ChenQiao-En LiuChung-Yen Liao
頁次 095-101
關鍵字 deep learningYoloOpen Street MapEIMEDLINEScopus
出刊日期 202102
DOI 10.3966/199115992021023201008

中文摘要

英文摘要

The purpose of this paper is to protect stray animals and reduce the social problems they cause through mobile devices. We wrote an app on the mobile device to explicitly identify the dog or cat. The system combined with the backend repository and placed the Open Street Map (OSM) to show the geographic location of the animal. Through this app, users can know where the stray animals are, which type, and what kind of assistance is needed. At the same time, if the user finds that there are stray animals in his location, but the APP does not display. The user can identify the animals through the system upload the location, type, and other issues to the database. In the part of the observation, we used You Look Only Once (Yolo) to train and put the training module into the system for the identification of stray animals with a precision of 95%. The system can reduce the problems caused by stray animals to increase the willingness of people to adopt stray animals and let shelter reduce the cost of dealing with stray animals.

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