3 accepted papers
Recent segmentation models have demonstrated promising efficiency by aggressively reducing parameter counts and computational complexity. However, these models often struggle to accurately delineate fine lesion boundaries and texture patterns essential for early skin cancer diagnosis and treatment p
Despite Siamese trackers’ substantial potential, they offer sub-optimal tracking performance in low-resolution (LR) contexts. We introduce a Random Noise Salient Feature Fusion Learning Network to address this issue. This method integrates random noise-infused feature maps into a similaritylearning…
Template learning transformer trackers have achieved significant performance improvement recently due to the longdependency learning using the self-attention (SA) mechanism. However, the typical SA mechanisms in transformers adopt a less discriminative design approach which is inadequate for focusin…