Classification of Watermelon Seeds Using Morphological Patterns of X-ray Imaging: A Comparison of Conventional Machine Learning and Deep Learning

Classification of Watermelon Seeds Using Morphological Patterns of X-ray Imaging: A Comparison of Conventional Machine Learning and Deep Learning

In this study, conventional machine learning and deep leaning approaches were evaluated using X-ray imaging techniques for investigating the internal parameters (endosperm and air space) of three cultivars of watermelon seed. In the conventional machine learning, six types of image features were ext...

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Bibliographic Details
Main Authors: Mohammed Raju Ahmed, Jannat Yasmin, Eunsung Park, Geonwoo Kim, Moon S. Kim, Collins Wakholi, Changyeun Mo, Byoung-Kwan Cho
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
seed quality
watermelon
X-ray imaging
image analysis
transfer learning
nondestructive measurement
Online Access:https://www.mdpi.com/1424-8220/20/23/6753

Internet

https://www.mdpi.com/1424-8220/20/23/6753

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