A hybrid deep learning-based fruit classification using attention model and convolution autoencoder

Image recognition supports several applications, for instance, facial recognition, image classification, and achieving accurate fruit and vegetable classification is very important in fresh supply chain, factories, supermarkets, and other fields. In this paper, we develop a hybrid deep learning-base...

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Veröffentlicht in:	Complex & intelligent systems Jg. 9; H. 3; S. 2209 - 2219
Hauptverfasser:	Xue, Gang, Liu, Shifeng, Ma, Yicao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.06.2023 Springer Nature B.V Springer
Schlagworte:	CBAM Classification Complexity Computational Intelligence Convolution Convolutional neural networks Data Structures and Information Theory Deep learning DenseNet Effectiveness Engineering Face recognition Factories Fruit classification Fruits Image classification Machine learning Original Article Supermarkets Supply chains DenseNet Fruit classification CBAM Convolutional neural networks
ISSN:	2199-4536, 2198-6053
Online-Zugang:	Volltext
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