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

Fast and accurate plant disease detection is critical to increasing agricultural productivity in
a sustainable way. Traditionally, human experts have been relied upon to diagnose …

Abstract We present Graph Neural Diffusion (GRAND) that approaches deep learning on
graphs as a continuous diffusion process and treats Graph Neural Networks (GNNs) as …

Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative
analysis of imaging data for biological and biomedical applications. Many bioimage analysis …

The rapid development of computer vision makes human-computer interaction possible and
has a wide application prospect. Since the discovery of the first case of COVID-19, the global …

Whole abdominal organ segmentation is important in diagnosing abdomen lesions,
radiotherapy, and follow-up. However, oncologists' delineating all abdominal organs from …

Published research results are difficult to replicate due to the lack of a standard evaluation
data set in the area of decision support systems in mammography; most computer-aided …

Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …

Saliency detection aims to highlight the most relevant objects in an image. Methods using
conventional models struggle whenever salient objects are pictured on top of a cluttered …

Partial differential equations (PDEs) are indispensable for modeling many physical
phenomena and also commonly used for solving image processing tasks. In the latter area …