Details

Autor(en) / Beteiligte

• Miao, Yujie
• Zhu, Shiping
• Pu, Jing
• Li, Junxian
• Ma, Lingkai
• Huang, Hua

Titel

Recognition of Furniture Wood Image Species Based on Convolutional Neural Networks

Ist Teil von

• Linye kexue (1979), 2023-01, Vol.59 (8), p.133

Ort / Verlag

Beijing: Chinese Society of Forestry

Erscheinungsjahr

2023

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• [Objective】 In order to solve the problems of strong subjectivity and low efficiency that the identification of furniture wood species mainly depends on manual identification in daily life, a common furniture wood species identification model based on Mobilenetv3 convolutional neural network（CNN） was designed to effectively improve the identification speed and accuracy of wood species. It provided a scientific and effective method for the rational utilization of wood resources, the management of wood import and export trade and the determination of furniture wood types by consumers.【Method】Firstly,3 880 images of four kinds of wood images coated without wood wax oil and two kinds of wood images coated with wood wax oil were collected. The data set was divided into training set, verification set and test set according to 6∶2∶2 and 2∶6∶2, and the data of the training set was expanded to four times of the original by using operations such as rotation and flip. Then four convolution neural networks and two tradit