In recent years, artificial intelligence (AI) technology has been used in most if not all domains
and has greatly benefited our lives. While AI can accurately extract critical features and …

Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

Computer vision has achieved remarkable success by (a) representing images as uniformly-
arranged pixel arrays and (b) convolving highly-localized features. However, convolutions …

In this paper, we study the context aggregation problem in semantic segmentation.
Motivated by that the label of a pixel is the category of the object that the pixel belongs to, we …

Transformer, first applied to the field of natural language processing, is a type of deep neural
network mainly based on the self-attention mechanism. Thanks to its strong representation …

In this paper, we address the semantic segmentation task with a new context aggregation
scheme named object context, which focuses on enhancing the role of object information …

Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …

Multi-scale inference is commonly used to improve the results of semantic segmentation.
Multiple images scales are passed through a network and then the results are combined …

Semantic segmentation of remote sensing images plays an important role in a wide range of
applications, including land resource management, biosphere monitoring, and urban …