成熟度
束
棕榈油
棕榈
机器视觉
图像处理
数学
计算机科学
园艺
人工智能
环境科学
成熟
生物
物理
光学
图像(数学)
农林复合经营
量子力学
梁(结构)
作者
Mohamed Yasser Mohamed Ahmed Mansour,Katrina D. Dambul,Kan Yeep Choo
出处
期刊:International Journal of Technology: IJ Tech
[International Journal of Technology]
日期:2022-11-03
卷期号:13 (6): 1326-1326
被引量:12
标识
DOI:10.14716/ijtech.v13i6.5932
摘要
Ripe oil palm fresh fruit bunch allows extraction of high-quality crude palm oil and kernel palm oil. As the fruit ripens, its surface color changes from black (unripe) or dark purple (unripe) to dark red (ripe). Thus, the surface color of the oil palm fresh fruit bunches may generally be used to indicate the maturity stage. Harvesting is commonly done by relying on human graders to harvest the bunches according to color and number of loose fruits on the ground. Non-destructive methods such as image processing and computer vision, including object detection algorithms have been proposed for the ripeness classification process. In this paper, several object detection algorithms were investigated to classify the ripeness of oil palm fresh fruit bunch. MobileNetV2 SSD, EfficientDet (Lite0, Lite1 and Lite2) and YOLOv5
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