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Table 2 Performance comparison between R-CNNGSR and the state-of-the-art methods

From: Region-based convolutional neural network using group sparse regularization for image sentiment classification

Methods	IAPS subset	Abstract	ArtPhoto	Emotion6
VGGNet	88.51	68.86	67.61	72.25
Fine-tuned VGGNet	89.37	72.48	70.09	77.02
PCNN	88.84	70.84	70.96	73.58
ARconcatenation	89.39	74.41	73.76	78.52
R-CNNGSR	92.14	75.89	75.02	81.36

Italics indicate the best of the accuracy evaluation in the five methods

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