In recent years, artificial intelligence (AI) has been increasingly put into use to address cities'
economic, social, environmental, and governance challenges. Thanks to its advanced …

Analyzing satellite images and remote sensing (RS) data using artificial intelligence (AI)
tools and data fusion strategies has recently opened new perspectives for environmental …

Among researchers using traditional and new machine learning and deep learning
techniques, 2D medical image segmentation models are popular. Additionally, 3D …

Land scene classification in satellite imagery has a wide range of applications in remote
surveillance, environment monitoring, remote scene analysis, Earth observations and urban …

Although the vision transformer-based methods (ViTs) exhibit an excellent performance than
convolutional neural networks (CNNs) for image recognition tasks, their pixel-level semantic …

Traditional models for semantic segmentation in point clouds primarily focus on smaller
scales. However, in real-world applications, point clouds often exhibit larger scales, leading …

Floods are the most frequent natural disasters, occurring almost every year around the
globe. To mitigate the damage caused by a flood, it is important to timely assess the …

The networks are required to be capable of learning low-level features well when applied to
remote sensing image (RSI) semantic segmentation tasks. To capture accurate and …

Land type survey is an important task of land resources survey and the basis of scientific
management of land resources. With the increasingly prominent problems of population …

Gliomas are the most common and highly growing tumors lead to high mortality rate in their
highest grade. The early diagnosis of gliomas, and treatment planning are most important …