[Retracted] A Wood Quality Defect Detection System Based on Deep Learning and Multicriterion Framework

Table 1

Comparison of engineering application efficiency of wood defect image reconstruction and quality evaluation model.

Compare items	Traditional wood quality grading system	Wood defect image reconstruction and quality evaluation model system based on deep reinforcement learning
Quality evaluation decision-making efficiency (%)	71.72	90.19
Image perception and reconstruction efficiency (s)	3.74	2.11
Decision system operation and maintenance loss performance (%)	12.14	2.23
Human-computer interaction friendliness of the system	Better	Very good
Defective image reconstruction effectiveness	Poor	Better
Internet push of quality evaluation information	Generally	Very good