IoT-Enabled Smart Solution for Rice Disease Detection, Yield Prediction, and Remediation-Reference-Cited by-同舟云学术

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IoT-Enabled Smart Solution for Rice Disease Detection, Yield Prediction, and Remediation

Published:2023-06-08 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)
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Author:

Wanninayake K.M.I.S¹,Bambaranda L.G.S. W¹,Wickramaarachchi T.I¹,Pathirana U.C.S.L¹,Vidhanaarachchi Samitha¹,Nanayakkara A.A.E.²,Gunapala K.R.D.³,Sarathchandra S.R.³,Gamage Aruna Ishara¹,De Silva D.I¹

Affiliation:

1. Sri Lanka Institute of Information Technology,Faculty of Computing,Malabe,Sri Lanka

2. University of Ruhuna,Faculty of Agriculture,Department of Soil Science,Sri Lanka

3. Rice Research and Development Institute,Bathalagoda,Ibbagamuwa,Sri Lanka

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10156655/10155769/10155770.pdf?arnumber=10155770

Reference24 articles.

1. Adoption and impact of modern rice varieties on poverty in eastern India;Rice Science,2019

2. Ship detection in optical sensing images based on YOLOv5

3. Overview of the yolo object detection algorithm;Medium,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DSC-T-Yolo-Rice: A Sand Clock Yolo Model for Rice Leaves Diseases Detection;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06

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