Fine-grained image classification model based on improved SqueezeNet

In order to solve the problem that some fine-grained algorithms have a large amount of calculation and low operating efficiency, This paper firstly proposes the use of SqueezeNet for fine-grained image recognition tasks, because SqueezeNet, as one of the representatives of lightweight CNN, has fewer...

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Bibliographic Details

Published in:	2021 IEEE 5th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) pp. 393 - 399
Main Authors:	Li, Mingyue, He, Lesheng, Lei, Chen, Gong, Youmei
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12-03-2021
Subjects:	attention mechanism feature fusion Fine-grained image classification Image classification Image recognition Kernel lightweight CNN Memory management SqueezeNet Task analysis Tensors Visualization
Online Access:	Get full text
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