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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KaLDeX integrates Kalman-filter linear deformable convolution and cross-attention inside UNet++ with persistent-homology loss, reporting higher accuracy than prior models on DRIVE, CHASE_DB1, STARE and OCTA-500 vessel datasets.
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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.