Early detection and assessment of polyps play a crucial role in the prevention and treatment
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …

The computational complexity of the self-attention mechanism in popular transformer
architectures poses significant challenges for training and inference, and becomes the …

Recent advancements in computational intelligence, deep learning, and computer-aided
detection have had a significant impact on the field of medical imaging. The task of image …

Simple Summary Transformer models, originally successful in natural language processing,
have found application in computer vision, demonstrating promising results in tasks related …

Object detection is a basic vision task that accompanies people's daily lives all the time. The
development of object detection technology has experienced an evolution from traditional …

Employing deep learning techniques for the semantic segmentation of remote sensing
images has emerged as a prevalent approach for acquiring information about water bodies …

Deep learning models often rely on a diverse and well-augmented dataset for optimal
performance. In this context, the methods of data augmentation are pivotal in boosting the …

Background Semantic segmentation plays an indispensable role in clinical diagnosis
support, intelligent surgical assistance, personalized treatment planning, and drug …

Skin cancer, a growing health concern, poses a significant threat. Automated segmentation
of skin lesions is crucial for precise clinical diagnosis and treatment. However, challenges …

Abstract Street View Imagery (SVI) is a valuable data source for studies (eg, environmental
assessments, green space identification or land cover classification). While commercial SVI …