In general, most of the existing convolutional neural network (CNN)-based deep-learning
models suffer from spatial-information loss and inadequate feature-representation issues …

The increasing popularity of attention mechanisms in deep learning algorithms for computer
vision and natural language processing made these models attractive to other research …

Real-time semantic segmentation provides precise insights into dynamic street
environments for autonomous driving, traffic control, and urban planning. However, state-of …

Breast cancer remains a critical global concern, underscoring the urgent need for early
detection and accurate diagnosis to improve survival rates among women. Recent …

Convolutional neural networks (CNN), especially numerous U-shaped models, have
achieved great progress in retinal vessel segmentation. However, a great quantity of global …

The nnUNet is a state-of-the-art deep learning based segmentation framework which
automatically and systematically configures the entire network training pipeline. We extend …

While vision transformers have been highly successful in improving the performance in
image-based tasks, not much work has been reported on applying transformers to scene text …

retinal image is a crucial window for the clinical observation of cardiovascular,
cerebrovascular, or other correlated diseases. Retinal vessel segmentation is of great …

The human brain is an incredible and wonderful organ that governs all body actions. Due to
its great importance, any defect in the shape of its regions should be reported quickly to …

Inland ponds exhibit remarkable ubiquity across the globe, playing a vital role in the
sustainability of global continental freshwater resources and contributing significantly to their …