A note on nilpotent subgroups of automorphism groups of RAAGs

Aramayona, Javier; Genevois, Anthony

doi:10.48550/arxiv.1803.08284

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Improvements On Senet For Large-scale Image Search1

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2024

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“…These methods involved random rotations, scaling, cropping, and horizontal flipping of images. By incorporating these modifications into the training data, the model is better equipped to handle various image transformations that may occur in real-world situations [10].…”

Section: Improvements On Senet For Large-scale Image Searchmentioning

confidence: 99%

Research On the Application of Improved Models Based on Senet in Large-Scale Image Retrieval Algorithms

Ren,

Sun

2024

HSET

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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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Section: Improvements On Senet For Large-scale Image Searchmentioning

confidence: 99%