Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign

Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign

This study systematically developed a deep transfer network for near-infrared spectrum detection using convolutional neural network modules as key components. Through meticulous evaluation, specific modules and structures suitable for constructing the near-infrared spectrum detection model were iden...

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Bibliographic Details
Main Authors: Dapeng Jiang, Keqi Wang, Hongbo Li, Yizhuo Zhang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Sensors
Subjects:
CNN
domain adaptation
near-infrared detection
nondestructive testing
transfer learning
wood material analysis
Online Access:https://www.mdpi.com/1424-8220/24/4/1245

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