Convolutional Neural Network Performance and the Factors Affecting Performance for Classification of Seven Quercus Species using Sclereid Characteristics in the Bark

Convolutional Neural Network Performance and the Factors Affecting Performance for Classification of Seven Quercus Species using Sclereid Characteristics in the Bark

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Based on the sclereids in the bark of oak species, a convolutional neural network (CNN) was employed to validate species classification performance and its influencing factors. Three optimizers including stochastic gradient descent (SGD), adaptive moment estimation (Adam), root mean square propagati...

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Bibliographic Details
Main Authors: Jong Ho Kim, Byantara Darsan Purusatama, Alvin Muhammad Savero, Denni Prasetia, Jae Hyuk Jang, Se Yeong Park, Seung Hwan Lee, Nam Hun Kim
Format: Article
Language:English
Published: North Carolina State University 2023-12-01
Series:BioResources
Subjects:
bark
convolutional neural networks (cnns)
oak
sclereids
species classification
Online Access:https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22966

Internet

https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22966

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