Using Fuzzy Mask R-CNN Model to Automatically Identify Tomato Ripeness

Using Fuzzy Mask R-CNN Model to Automatically Identify Tomato Ripeness

Manual inspection and harvesting of ripening tomatoes is time consuming and labor intensive. Smart agriculture can emphasize the use of digital horticultural resources for farming and can increase farm sustainability; to that end, we proposed a fuzzy Mask R-CNN model to automatically identify the ri...

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Bibliographic Details
Main Authors: Yo-Ping Huang, Tzu-Hao Wang, Haobijam Basanta
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Automatic annotation
detection of tomato ripeness
fuzzy c-means
Mask Region-based Convolutional Neural Network (Mask R-CNN)
hue > saturation > value (HSV) color model
Online Access:https://ieeexplore.ieee.org/document/9260129/

Internet

https://ieeexplore.ieee.org/document/9260129/

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