Tag: Vision Transformers

A systematic review of 168 primary studies found that 57.14% did not examine the performance–faithfulness relationship, 41.07% reported synergy and ...

A 2026 review finds that dataset diversity, annotation quality and external validation remain major barriers to reliable clinical generalization of ...

A hybrid deep learning framework combining Siamese networks and Vision Transformers achieves up to 95 percent accuracy in verifying parent-child ...

A systematic review of 284 studies maps how AI is transforming breast cancer imaging, from CNN detection and foundation-model segmentation ...

A new review in the Journal of Neuro-Oncology finds that machine learning, especially multimodal AI, is transforming brain cancer outcome ...

A controlled head-to-head study shows Vision Transformers beat convolutional networks on real X-ray diffraction data once fine-tuned, while CNNs remain ...

Researchers at ETH Zürich have shown that self-supervised pretraining on simulated detector data can teach a single neural encoder to ...

A comprehensive new review in Neural Computing and Applications charts how machine learning and deep learning are transforming lymphoma diagnosis ...

Researchers have combined convolutional neural networks and vision transformers with a three-loss training strategy to significantly improve content-based image retrieval ...

A new study of ensemble deep learning on medical image benchmarks shows that the most accurate models are rarely the ...