Aiming at the problems of low accuracy and small sample size of petroleum coke and metallurgical coke microscopic image classification,this paper proposes an image classification model of petroleum coke and metallurgical coke based on ResNet.By using the pre-trained model on the large-scale ImageNet dataset,a better feature representation is obtained.The experiment compared the classification performance of different layers of ResNet,and compared the classification effect before and after the training model,and determined the advantages of ResNet-50 in handling this classification task.ResNet-50 is compared and analyzed with other deep learning models,and the results of the study show that ResNet-50,in combination with a pre-trained model,is able to accurately differentiate between the two coke types with good robustness.
维普
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