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The outcomes indicated that tree species identification derived through the trained convolutional neural system models had been reliable, because of the GoogLeNet and LeNet revealed the highest (96.7%) and most affordable (66.4%) identification reliability. The tree species identifications using different types were very consistent. Quercus mongolica and Abies nephrolepis revealed the greatest (100% for AlexNet) and least expensive identification reliability, respectively. Misidentification could occur
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