Fisher vector encoding integrated into CNN-ViT hybrids outperforms benchmarks on MedMNIST datasets and matches literature results on other medical image sets.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Convolutional autoencoder pretraining plus deep filter banks and Fisher vector pooling yields improved texture classification accuracy and lower complexity than transformer-based masked autoencoders on standard texture datasets.
citing papers explorer
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Deep neural networks with Fisher vector encoding for medical image classification
Fisher vector encoding integrated into CNN-ViT hybrids outperforms benchmarks on MedMNIST datasets and matches literature results on other medical image sets.
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A self-supervised learning approach to deep filter banks for texture recognition
Convolutional autoencoder pretraining plus deep filter banks and Fisher vector pooling yields improved texture classification accuracy and lower complexity than transformer-based masked autoencoders on standard texture datasets.