Artwork Style Recognition Using Vision Transformers and MLP Mixer

Iliadis, Lazaros Alexios; Nikolaidis, S.; Sarigiannidis, Panagiotis; Wan, Shaohua; Goudos, Sotirios K.

doi:10.3390/technologies10010002

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…MS-MLP [47] is used for ECG classification. In [48], MLP-Mixer was used for artistic style classification. Moreover, Wang [49] successfully detected Alzheimer's disease through MLP.…”

Section: Related Workmentioning

confidence: 99%

Representation Learning Method for Circular Seal Based on Modified MLP-Mixer

Cao,

Zhou,

Zhang

et al. 2023

Entropy

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This study proposes Stamp-MLP, an enhanced seal impression representation learning technique based on MLP-Mixer. Instead of using the patch linear mapping preprocessing method, this technique uses circular seal remapping, which reserves the seals’ underlying pixel-level information. In the proposed Stamp-MLP, the average pooling is replaced by a global pooling of attention to extract the information more comprehensively. There were three classification tasks in our proposed method: categorizing the seal surface, identifying the product type, and distinguishing individual seals. The three tasks shared an identical dataset comprising 81 seals, encompassing 16 distinct seal surfaces, with each surface featuring six diverse product types. The experiment results showed that, in comparison to MLP-Mixer, VGG16, and ResNet50, the proposed Stamp-MLP achieved the highest classification accuracy (89.61%) in seal surface classification tasks with fewer training samples. Meanwhile, Stamp-MLP outperformed the others with accuracy rates of 90.68% and 91.96% in the product type and seal impression classification tasks, respectively. Moreover, Stamp-MLP had the fewest model parameters (2.67 M).

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“…MS-MLP [47] is used for ECG classification. In [48], MLP-Mixer was used for artistic style classification. Moreover, Wang [49] successfully detected Alzheimer's disease through MLP.…”

Section: Related Workmentioning

confidence: 99%

Representation Learning Method for Circular Seal Based on Modified MLP-Mixer

Cao,

Zhou,

Zhang

et al. 2023

Entropy

View full text Add to dashboard Cite

show abstract

“…Paper [10] presents an AI-based system able to recognize the art style of a work. The paper presents two different Deep Learning architectures-Vision Transformer and MLP Mixer (Multi-layer Perceptron Mixer)-trained from scratch in the task of artwork style recognition, achieving over 39% prediction accuracy for 21 style classes on the WikiArt paintings dataset.…”

mentioning

confidence: 99%