Research on Lightweight Model of Post-training Pruning of Knowledge-transferred DenseNet for Social Insects Identification
The rapid and effective identification of populations such as bees and ants,which have significant eco-logical impacts,on resource-constrained devices holds great ecological conservation significance.In this paper,a DenseNet pre-trained model is employed for knowledge transfer on a small-scale dataset of ants and bees,and an unstructured post-training pruning method known as UPSCALE is utilized to construct a comprehensive framework.Experimental results demonstrate that this framework can rapidly leverage small-scale datasets to achieve target image recognition with high accuracy,while the model parameters are less than one-third of those of the baseline method,thus providing broader application value for deployment on devices.
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