Sustainable Oil Palm Resource Assessment Based on an Enhanced Deep Learning Method
Knowledge of the number and distribution of oil palm trees during the crop cycle is vital for sustainable management and predicting yields. The accuracy of the conventional image processing method is limited for the hand-crafted feature extraction method and the overfitting problem occurs due to the...
Main Authors: | Xinni Liu, Kamarul H. Ghazali, Akeel A. Shah |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-06-01
|
Series: | Energies |
Subjects: | |
Online Access: | https://www.mdpi.com/1996-1073/15/12/4479 |
Similar Items
-
Oil Palm Tree Detection and Health Classification on High-Resolution Imagery Using Deep Learning
by: Kanitta Yarak, et al.
Published: (2021-02-01) -
Deep learning applications for oil palm tree detection and counting
by: Kuryati Kipli, et al.
Published: (2023-10-01) -
Evaluating the effectiveness of palm oil certification in delivering multiple sustainability objectives
by: Courtney L Morgans, et al.
Published: (2018-01-01) -
Peeling back the label—exploring sustainable palm oil ecolabelling and consumption in the United Kingdom
by: Rosemary Ostfeld, et al.
Published: (2019-01-01) -
SSR mining in oil palm EST database: application in oil palm germplasm diversity studies.
by: Ngoot-Chin, Ting, et al.
Published: (2010)