Tag: Vision Transformers

A survey published in Artificial Intelligence Review introduces a formal framework linking diverse computer vision architectures and training objectives through ...

Researchers have shown that randomly shuffling embedded patch tokens inside vision transformer surrogate models during adversarial example generation substantially improves ...

An explainable transformer model fusing MRI with texture descriptors reached over 99 percent accuracy in Alzheimer's disease staging benchmarks, with ...

Self-supervised foundation models pretrained on nearly 1.8 million unlabeled cell images outperformed the classical CellProfiler pipeline at retrieving compound replicates ...

A new review in Chinese Medical Journal maps deep learning architectures to core clinical tasks in pathology, highlighting accuracy gains, ...

A new review argues that deep learning skin lesion analysis must prove itself through external validation, fairness and clinical utility ...

Researchers developed a Shapley-guided token pruning method that significantly reduces latency and energy consumption in Vision Transformers for remote sensing ...

A systematic review finds deep learning exceeds 97 percent accuracy on remote sensing benchmarks but struggles with generalization, spectral exploitation ...

An experimental graphene optical system uses red, green and blue light challenges, transformer-assisted image analysis and binary codes to create ...

A frequency-aware sparse vision transformer outperformed comparison models on organ, cardiac, breast, skin and polyp segmentation across five public medical ...