Predicting Calamansi Fruit Yield Using CNN-Based Flower Detection: A Deep Learning Approach
Author:
Affiliation:
1. Graduate School, Technological Institute of the Philippines,Manila,Philippines
2. College of Computing Science, Isabela State University,Cauayan Campus,Isabela,Philippines
Funder
Commission on Higher Education (CHED)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10613603/10613624/10613627.pdf?arnumber=10613627
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4. Crop Yield Prediction using Machine Learning and Deep Learning Techniques;Jhajharia;Procedia Computer Science,2023
5. Incidence mapping of Calamansi pests and diseases in Victoria, Oriental Mindoro through Geographic Information System (GIS);Ramos;CLSU International Journal of Science and Technology,2021
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