U Shaped

U-shaped architectures, characterized by their encoder-decoder structure with skip connections, are a dominant theme in various image processing and time series analysis tasks. Current research focuses on enhancing these architectures through the integration of transformers, attention mechanisms, and novel modules like large kernels or gated networks to improve feature extraction, long-range dependency modeling, and computational efficiency across diverse applications such as medical image segmentation, deblurring, and speech enhancement. These advancements are significantly impacting fields like medical imaging and autonomous systems by enabling more accurate, efficient, and robust algorithms for tasks requiring detailed spatial or temporal understanding.