Transformers have shown great promise in medical image segmentation due to their ability
to capture long-range dependencies through self-attention. However, they lack the ability to …

Deep learning-based segmentation of very high-resolution (VHR) satellite images is a
significant task providing valuable information for various geospatial applications …

Segmentation of skin lesions is a challenging task because of the wide range of skin lesion
shapes, sizes, colors, and texture types. In the past few years, deep learning networks such …

Roads are the fundamental elements of transportation, connecting cities and rural areas, as
well as people's lives and work. They play a significant role in various areas such as map …

The inability of conventional algorithms to detect infrared (IR) ship targets in complex scenes
led to the development of detection methods based on convolutional neural networks …

Simple Summary Prostate cancer represents a highly prevalent form of cancer worldwide,
with timely detection and treatment being crucial for achieving a high survival rate. Manual …

Although deep learning-based methods for semantic segmentation have achieved
prominent performance in the general image domain, semantic segmentation for high …

Site-specific crop management in heterogeneous fields has emerged as a promising
avenue towards increasing agricultural productivity whilst safeguarding the environment …

As a cutting-edge challenge in the field of disaster evaluation, the detection of disasters in
remote sensing images is crucial. However, most existing approaches to disaster detection …

Detecting early plant diseases autonomously poses a significant challenge for self-
navigating robots and automated systems utilizing Artificial Intelligence (AI) imaging. For …