Research on forest pest identification method based on face image quality assessment
To solve the above problems,we propose a ResNet-based quality assessment method for pest images to pre-evaluate forestry pest images.The method first extracts pest image features and calculates the similar distribution distance between different image features as quality pseudo-labels for training by Wasserstein distance.Then,different quality forestry pest images are distinguished by pre-evaluation and screened for recognition classification to improve recognition accuracy.The experimental results show that the recognition accuracy of the forest pest dataset screened by this method is improved by 2.97%and 2.57%on the ResNet18 and the ResNet50 networks,respectively.
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