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https://elib.vku.udn.vn/handle/123456789/1895
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DC Field | Value | Language |
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dc.contributor.author | Bui, Xuan Thien | - |
dc.contributor.author | Pham, Vu Thu Nguyet | - |
dc.contributor.author | Bui, Chuyen Van | - |
dc.contributor.author | Nguyen, Lao | - |
dc.contributor.author | Nguyen, Ha Huy Cuong | - |
dc.date.accessioned | 2021-12-27T09:43:46Z | - |
dc.date.available | 2021-12-27T09:43:46Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://elib.vku.udn.vn/handle/123456789/1895 | - |
dc.description | The 10th Conference on Information Technology and its Applications; Topic: Data Science and AI; Poster; pp. 2-10. | vi_VN |
dc.description.abstract | Artificial Intelligence is being widely applied in many fields during the Fourth Industrial Revolution. However, in the current agricultural model, humans are still used as the primary labor force, which is costly in terms of both finance and human resources. Furthermore, the typical fruits of each region, particularly pineapple, have a rather complicated ripening period. Controlling and managing hundreds of hectares of land is difficult. So that, in this paper, we propose using deep learning models to assist in identifying and detecting the growth stages of pineapples in order to ensure that care and harvesting are completed on time. | vi_VN |
dc.language.iso | en | vi_VN |
dc.publisher | Da Nang Publishing House | vi_VN |
dc.subject | Yolov4 | vi_VN |
dc.subject | CNN | vi_VN |
dc.subject | Deep Learning | vi_VN |
dc.subject | Machine Learning | vi_VN |
dc.subject | Pineapple | vi_VN |
dc.title | Automatic Detection of Pineapple's Growth Stage using Deep Learning | vi_VN |
dc.type | Working Paper | vi_VN |
Appears in Collections: | CITA 2021 |
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