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A Novel Method in wood Identification Based on Anatomical Image Using Hybrid Model

Computer Systems Science & Engineering 2023年第11期47卷 2381-2396页

作者： Nguyen Minh Trieu Nguyen Truong Thinh College of Technology and Design University of Economics Ho Chi Minh City—UEHHo Chi Minh City72516Vietnam

Nowadays,wood identification is made by experts using hand lenses,wood atlases,and field manuals which take a lot of cost and time for the training *** quantity and species must be strictly set up,and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal *** the development of science,wood identification should be supported with technology to enhance the perception of fairness of *** automatic wood identification system and a dataset of 50 commercial wood species from Asia are established,namely,wood anatomical images collected and used to train for the proposed *** the convolutional neural network(CNN),the last layers are usually soft-max functions with dense *** layers contain the most parameters that affect the speed *** reduce the number of parameters in the last layers of the CNN model and enhance the accuracy,the structure of the model should be optimized and ***,a hybrid of convolutional neural network and random forest model(CNN-RF model)is introduced to wood *** accuracy’s hybrid model is more than 98%,and the processing speed is 3 times higher than the CNN *** highest accuracy is 1.00 in some species,and the lowest is *** results show the excellent adaptability of the hybrid model in wood identification based on anatomical *** also facilitates further investigations of wood cells and has implications for wood science.

关键词： identifying wood anatomical wood hybrid model CNN-RF automatic identification vietnam wood

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