Utilizing UAV-based multispectral imagery and convolutional neural networks for brix value prediction
Authors
W. A. N. M. Perera
managingeditor.cjs@sci.pdn.ac.lk
Sabaragamuwa University of Sri Lanka, Belihuloya 70140
P. A. D. V. Vithanage
managingeditor.cjs@sci.pdn.ac.lk
Sabaragamuwa University of Sri Lanka, Belihuloya 70140
R. M. D. Jayathilake
managingeditor.cjs@sci.pdn.ac.lk
University of Derby, Kedleston Road, Derby. DE22 1GB
Saitama University, Sakura-ku, Saitama City, Saitama 338-8570
L. L. G. Chathuranga
managingeditor.cjs@sci.pdn.ac.lk
Sabaragamuwa University of Sri Lanka, Belihuloya 70140
L. L. G. Chathuranga
managingeditor.cjs@sci.pdn.ac.lk
Sabaragamuwa University of Sri Lanka, Belihuloya 70140
R. M. K. T. Rathnayaka
managingeditor.cjs@sci.pdn.ac.lk
Sabaragamuwa University of Sri Lanka, Belihuloya 70140
DOI: https://doi.org/10.4038/cjs.v55i2.8865 | Journal eISSN: 2513-230X
Language: English
Page range: 592 - 601
Published on: May 21, 2026
Published by: Faculty of Science, University of Peradeniya, Sri Lanka
In partnership with: Paradigm Publishing Services
Keywords:
© 2026 W. A. N. M. Perera, P. A. D. V. Vithanage, R. M. D. Jayathilake, W. P. R. Welihinda, W. M. C. J. T. Kithulwatta, L. L. G. Chathuranga, L. L. G. Chathuranga, D. M. K. N. Seneviratna, R. M. K. T. Rathnayaka, published by Faculty of Science, University of Peradeniya, Sri Lanka
This work is licensed under the Creative Commons Attribution 4.0 License.