Research On the Application of Improved Models Based on Senet in Large-Scale Image Retrieval Algorithms
DOI:
https://doi.org/10.54097/c5kbeg66Keywords:
Large-scale image retrieval, SENet, Data Augmentation, Regularization, Transfer Learning.Abstract
The proliferation of the Internet has led to a significant increase in image data, prompting a surge of interest in large-scale image retrieval technology. This study introduces an image retrieval algorithm leveraging SENet, incorporating data augmentation and regularization techniques to bolster model generalization capabilities, and employing transfer learning to enhance initial performance. Experimental findings demonstrate that this algorithm successfully enhances the accuracy and efficiency of image retrieval.
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